Run
9204186

Run 9204186

Task 3573 (Supervised Classification) mnist_784 Uploaded 11-07-2018 by Irfan Nur Afif
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPo oling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Co ncatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling 2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concate nate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,C onv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate, Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)Automatically created scikit-learn flow.
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_batch_size32
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_build_fn{"oml-python:serialized_object": "function", "value": "__main__.squeezenet_mnist_fmnist_5_32_False"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_epochs5
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer0{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 784], "dtype": "float32", "name": "input", "sparse": false}, "inbound_nodes": [], "name": "input"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer1{"class_name": "Reshape", "config": {"name": "reshape_6", "target_shape": [28, 28, 1], "trainable": false}, "inbound_nodes": [[["input", 0, 0, {}]]], "name": "reshape_6"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer10{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 64, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_52", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_51", 0, 0, {}]]], "name": "conv2d_52"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer11{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 64, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [3, 3], "name": "conv2d_53", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_51", 0, 0, {}]]], "name": "conv2d_53"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer12{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_10", "trainable": false}, "inbound_nodes": [[["conv2d_52", 0, 0, {}], ["conv2d_53", 0, 0, {}]]], "name": "concatenate_10"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer13{"class_name": "Activation", "config": {"activation": "linear", "name": "activation_10", "trainable": false}, "inbound_nodes": [[["concatenate_10", 0, 0, {}]]], "name": "activation_10"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer14{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 32, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_54", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["activation_10", 0, 0, {}]]], "name": "conv2d_54"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer15{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 128, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_55", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_54", 0, 0, {}]]], "name": "conv2d_55"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer16{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 128, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [3, 3], "name": "conv2d_56", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_54", 0, 0, {}]]], "name": "conv2d_56"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer17{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_11", "trainable": false}, "inbound_nodes": [[["conv2d_55", 0, 0, {}], ["conv2d_56", 0, 0, {}]]], "name": "concatenate_11"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer18{"class_name": "Activation", "config": {"activation": "linear", "name": "activation_11", "trainable": false}, "inbound_nodes": [[["concatenate_11", 0, 0, {}]]], "name": "activation_11"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer19{"class_name": "MaxPooling2D", "config": {"data_format": "channels_last", "name": "max_pooling2d_17", "padding": "valid", "pool_size": [2, 2], "strides": [2, 2], "trainable": false}, "inbound_nodes": [[["activation_11", 0, 0, {}]]], "name": "max_pooling2d_17"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer2{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 96, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [3, 3], "name": "conv2d_47", "padding": "valid", "strides": [2, 2], "trainable": false, "use_bias": true}, "inbound_nodes": [[["reshape_6", 0, 0, {}]]], "name": "conv2d_47"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer20{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 32, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_57", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["max_pooling2d_17", 0, 0, {}]]], "name": "conv2d_57"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer21{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 128, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_58", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_57", 0, 0, {}]]], "name": "conv2d_58"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer22{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 128, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [3, 3], "name": "conv2d_59", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_57", 0, 0, {}]]], "name": "conv2d_59"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer23{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_12", "trainable": false}, "inbound_nodes": [[["conv2d_58", 0, 0, {}], ["conv2d_59", 0, 0, {}]]], "name": "concatenate_12"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer24{"class_name": "Activation", "config": {"activation": "linear", "name": "activation_12", "trainable": false}, "inbound_nodes": [[["concatenate_12", 0, 0, {}]]], "name": "activation_12"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer25{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 48, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_60", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["activation_12", 0, 0, {}]]], "name": "conv2d_60"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer26{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 192, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_61", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_60", 0, 0, {}]]], "name": "conv2d_61"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer27{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 192, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [3, 3], "name": "conv2d_62", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_60", 0, 0, {}]]], "name": "conv2d_62"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer28{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_13", "trainable": false}, "inbound_nodes": [[["conv2d_61", 0, 0, {}], ["conv2d_62", 0, 0, {}]]], "name": "concatenate_13"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer29{"class_name": "Activation", "config": {"activation": "linear", "name": "activation_13", "trainable": false}, "inbound_nodes": [[["concatenate_13", 0, 0, {}]]], "name": "activation_13"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer3{"class_name": "MaxPooling2D", "config": {"data_format": "channels_last", "name": "max_pooling2d_16", "padding": "valid", "pool_size": [2, 2], "strides": [2, 2], "trainable": false}, "inbound_nodes": [[["conv2d_47", 0, 0, {}]]], "name": "max_pooling2d_16"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer30{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 48, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_63", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["activation_13", 0, 0, {}]]], "name": "conv2d_63"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer31{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 192, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_64", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_63", 0, 0, {}]]], "name": "conv2d_64"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer32{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 192, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [3, 3], "name": "conv2d_65", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_63", 0, 0, {}]]], "name": "conv2d_65"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer33{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_14", "trainable": false}, "inbound_nodes": [[["conv2d_64", 0, 0, {}], ["conv2d_65", 0, 0, {}]]], "name": "concatenate_14"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer34{"class_name": "Activation", "config": {"activation": "linear", "name": "activation_14", "trainable": false}, "inbound_nodes": [[["concatenate_14", 0, 0, {}]]], "name": "activation_14"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer35{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 64, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_66", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["activation_14", 0, 0, {}]]], "name": "conv2d_66"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer36{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 256, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_67", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_66", 0, 0, {}]]], "name": "conv2d_67"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer37{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 256, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [3, 3], "name": "conv2d_68", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_66", 0, 0, {}]]], "name": "conv2d_68"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer38{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_15", "trainable": false}, "inbound_nodes": [[["conv2d_67", 0, 0, {}], ["conv2d_68", 0, 0, {}]]], "name": "concatenate_15"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer39{"class_name": "Activation", "config": {"activation": "linear", "name": "activation_15", "trainable": false}, "inbound_nodes": [[["concatenate_15", 0, 0, {}]]], "name": "activation_15"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer4{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 16, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_48", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["max_pooling2d_16", 0, 0, {}]]], "name": "conv2d_48"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer40{"class_name": "MaxPooling2D", "config": {"data_format": "channels_last", "name": "max_pooling2d_18", "padding": "valid", "pool_size": [2, 2], "strides": [2, 2], "trainable": false}, "inbound_nodes": [[["activation_15", 0, 0, {}]]], "name": "max_pooling2d_18"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer41{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 64, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_69", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["max_pooling2d_18", 0, 0, {}]]], "name": "conv2d_69"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer42{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 256, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_70", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_69", 0, 0, {}]]], "name": "conv2d_70"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer43{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 256, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [3, 3], "name": "conv2d_71", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_69", 0, 0, {}]]], "name": "conv2d_71"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer44{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_16", "trainable": false}, "inbound_nodes": [[["conv2d_70", 0, 0, {}], ["conv2d_71", 0, 0, {}]]], "name": "concatenate_16"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer45{"class_name": "Activation", "config": {"activation": "linear", "name": "activation_16", "trainable": false}, "inbound_nodes": [[["concatenate_16", 0, 0, {}]]], "name": "activation_16"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer46{"class_name": "Dropout", "config": {"name": "dropout_10", "noise_shape": null, "rate": 0.5, "seed": null, "trainable": false}, "inbound_nodes": [[["activation_16", 0, 0, {}]]], "name": "dropout_10"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer47{"class_name": "Conv2D", "config": {"activation": "linear", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 10, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_72", "padding": "valid", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["dropout_10", 0, 0, {}]]], "name": "conv2d_72"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer48{"class_name": "AveragePooling2D", "config": {"data_format": "channels_last", "name": "average_pooling2d_2", "padding": "same", "pool_size": [13, 13], "strides": [1, 1], "trainable": false}, "inbound_nodes": [[["conv2d_72", 0, 0, {}]]], "name": "average_pooling2d_2"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer49{"class_name": "Flatten", "config": {"data_format": "channels_last", "name": "flatten_6", "trainable": false}, "inbound_nodes": [[["average_pooling2d_2", 0, 0, {}]]], "name": "flatten_6"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer5{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 64, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_49", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_48", 0, 0, {}]]], "name": "conv2d_49"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer50{"class_name": "Dense", "config": {"activation": "softmax", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "name": "dense_14", "trainable": true, "units": 10, "use_bias": true}, "inbound_nodes": [[["flatten_6", 0, 0, {}]]], "name": "dense_14"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer6{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 64, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [3, 3], "name": "conv2d_50", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["conv2d_48", 0, 0, {}]]], "name": "conv2d_50"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer7{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_9", "trainable": false}, "inbound_nodes": [[["conv2d_49", 0, 0, {}], ["conv2d_50", 0, 0, {}]]], "name": "concatenate_9"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer8{"class_name": "Activation", "config": {"activation": "linear", "name": "activation_9", "trainable": false}, "inbound_nodes": [[["concatenate_9", 0, 0, {}]]], "name": "activation_9"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_layer9{"class_name": "Conv2D", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "data_format": "channels_last", "dilation_rate": [1, 1], "filters": 16, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "kernel_size": [1, 1], "name": "conv2d_51", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["activation_9", 0, 0, {}]]], "name": "conv2d_51"}
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Dropout,Conv2D,AveragePooling2D,Flatten,Dense)(1)_verbose2

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

Area under ROC curve
0.9552 ± 0.0019
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7298 ± 0.007
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.7009 ± 0.0079
Cross-validation details (10-fold Crossvalidation)
KB relative information score
45184.1053 ± 28.5805
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0914 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1799 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
70000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7292 ± 0.0073
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7309 ± 0.0071
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3198
Cross-validation details (10-fold Crossvalidation)
Recall
0.7309 ± 0.0071
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5077 ± 0.0038
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1985 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6616 ± 0.0043
Cross-validation details (10-fold Crossvalidation)