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9204122

Run 9204122

Task 168294 (Supervised Classification) EMNIST_Balanced Uploaded 05-07-2018 by Irfan Nur Afif
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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_size1024
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"}
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)_epochs3
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_1", "target_shape": [28, 28, 1], "trainable": true}, "inbound_nodes": [[["input", 0, 0, {}]]], "name": "reshape_1"}
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_6", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_5", 0, 0, {}]]], "name": "conv2d_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)_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_7", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_5", 0, 0, {}]]], "name": "conv2d_7"}
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_2", "trainable": true}, "inbound_nodes": [[["conv2d_6", 0, 0, {}], ["conv2d_7", 0, 0, {}]]], "name": "concatenate_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)_layer13{"class_name": "Activation", "config": {"activation": "linear", "name": "activation_2", "trainable": true}, "inbound_nodes": [[["concatenate_2", 0, 0, {}]]], "name": "activation_2"}
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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_10", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_8", 0, 0, {}]]], "name": "conv2d_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)_layer17{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_3", "trainable": true}, "inbound_nodes": [[["conv2d_9", 0, 0, {}], ["conv2d_10", 0, 0, {}]]], "name": "concatenate_3"}
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_3", "trainable": true}, "inbound_nodes": [[["concatenate_3", 0, 0, {}]]], "name": "activation_3"}
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_2", "padding": "valid", "pool_size": [2, 2], "strides": [2, 2], "trainable": true}, "inbound_nodes": [[["activation_3", 0, 0, {}]]], "name": "max_pooling2d_2"}
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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_4", "trainable": true}, "inbound_nodes": [[["conv2d_12", 0, 0, {}], ["conv2d_13", 0, 0, {}]]], "name": "concatenate_4"}
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_4", "trainable": true}, "inbound_nodes": [[["concatenate_4", 0, 0, {}]]], "name": "activation_4"}
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_14", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["activation_4", 0, 0, {}]]], "name": "conv2d_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)_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_15", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_14", 0, 0, {}]]], "name": "conv2d_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)_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_16", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_14", 0, 0, {}]]], "name": "conv2d_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)_layer28{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_5", "trainable": true}, "inbound_nodes": [[["conv2d_15", 0, 0, {}], ["conv2d_16", 0, 0, {}]]], "name": "concatenate_5"}
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_5", "trainable": true}, "inbound_nodes": [[["concatenate_5", 0, 0, {}]]], "name": "activation_5"}
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_1", "padding": "valid", "pool_size": [2, 2], "strides": [2, 2], "trainable": true}, "inbound_nodes": [[["conv2d_1", 0, 0, {}]]], "name": "max_pooling2d_1"}
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_17", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["activation_5", 0, 0, {}]]], "name": "conv2d_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)_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_18", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_17", 0, 0, {}]]], "name": "conv2d_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)_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_19", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_17", 0, 0, {}]]], "name": "conv2d_19"}
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_6", "trainable": true}, "inbound_nodes": [[["conv2d_18", 0, 0, {}], ["conv2d_19", 0, 0, {}]]], "name": "concatenate_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)_layer34{"class_name": "Activation", "config": {"activation": "linear", "name": "activation_6", "trainable": true}, "inbound_nodes": [[["concatenate_6", 0, 0, {}]]], "name": "activation_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)_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_20", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["activation_6", 0, 0, {}]]], "name": "conv2d_20"}
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_21", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_20", 0, 0, {}]]], "name": "conv2d_21"}
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_22", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_20", 0, 0, {}]]], "name": "conv2d_22"}
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_7", "trainable": true}, "inbound_nodes": [[["conv2d_21", 0, 0, {}], ["conv2d_22", 0, 0, {}]]], "name": "concatenate_7"}
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_7", "trainable": true}, "inbound_nodes": [[["concatenate_7", 0, 0, {}]]], "name": "activation_7"}
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_2", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["max_pooling2d_1", 0, 0, {}]]], "name": "conv2d_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)_layer40{"class_name": "MaxPooling2D", "config": {"data_format": "channels_last", "name": "max_pooling2d_3", "padding": "valid", "pool_size": [2, 2], "strides": [2, 2], "trainable": true}, "inbound_nodes": [[["activation_7", 0, 0, {}]]], "name": "max_pooling2d_3"}
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_23", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["max_pooling2d_3", 0, 0, {}]]], "name": "conv2d_23"}
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_24", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_23", 0, 0, {}]]], "name": "conv2d_24"}
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_25", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_23", 0, 0, {}]]], "name": "conv2d_25"}
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_8", "trainable": true}, "inbound_nodes": [[["conv2d_24", 0, 0, {}], ["conv2d_25", 0, 0, {}]]], "name": "concatenate_8"}
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_8", "trainable": true}, "inbound_nodes": [[["concatenate_8", 0, 0, {}]]], "name": "activation_8"}
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_1", "noise_shape": null, "rate": 0.5, "seed": null, "trainable": true}, "inbound_nodes": [[["activation_8", 0, 0, {}]]], "name": "dropout_1"}
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_26", "padding": "valid", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["dropout_1", 0, 0, {}]]], "name": "conv2d_26"}
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_1", "padding": "same", "pool_size": [13, 13], "strides": [1, 1], "trainable": true}, "inbound_nodes": [[["conv2d_26", 0, 0, {}]]], "name": "average_pooling2d_1"}
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_1", "trainable": true}, "inbound_nodes": [[["average_pooling2d_1", 0, 0, {}]]], "name": "flatten_1"}
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_3", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_2", 0, 0, {}]]], "name": "conv2d_3"}
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_1", "trainable": true, "units": 47, "use_bias": true}, "inbound_nodes": [[["flatten_1", 0, 0, {}]]], "name": "dense_1"}
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_4", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_2", 0, 0, {}]]], "name": "conv2d_4"}
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_1", "trainable": true}, "inbound_nodes": [[["conv2d_3", 0, 0, {}], ["conv2d_4", 0, 0, {}]]], "name": "concatenate_1"}
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_1", "trainable": true}, "inbound_nodes": [[["concatenate_1", 0, 0, {}]]], "name": "activation_1"}
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_5", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["activation_1", 0, 0, {}]]], "name": "conv2d_5"}
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
0.9838 ± 0.0049
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.6593 ± 0.0803
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6541 ± 0.0794
Cross-validation details (10-fold Crossvalidation)
KB relative information score
98134.7212 ± 835.9512
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0194 ± 0.0039
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0416
Cross-validation details (10-fold Crossvalidation)
Number of instances
131600
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6668 ± 0.0484
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.6615 ± 0.0777
Cross-validation details (10-fold Crossvalidation)
Prior entropy
5.5546
Cross-validation details (10-fold Crossvalidation)
Recall
0.6615 ± 0.0777
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4667 ± 0.0938
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.1443
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0985 ± 0.0101
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6826 ± 0.0701
Cross-validation details (10-fold Crossvalidation)