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9204213

Run 9204213

Task 3573 (Supervised Classification) mnist_784 Uploaded 16-07-2018 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_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_5", "target_shape": [28, 28, 1], "trainable": true}, "inbound_nodes": [[["input", 0, 0, {}]]], "name": "reshape_5"}
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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)_layer17{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_3", "trainable": true}, "inbound_nodes": [[["conv2d_29", 0, 0, {}], ["conv2d_30", 0, 0, {}]]], "name": "concatenate_3"}
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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_32", 0, 0, {}], ["conv2d_33", 0, 0, {}]]], "name": "concatenate_4"}
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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)_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_34", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["activation_4", 0, 0, {}]]], "name": "conv2d_34"}
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_35", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_34", 0, 0, {}]]], "name": "conv2d_35"}
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_36", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_34", 0, 0, {}]]], "name": "conv2d_36"}
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_35", 0, 0, {}], ["conv2d_36", 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_13", "padding": "valid", "pool_size": [2, 2], "strides": [2, 2], "trainable": true}, "inbound_nodes": [[["conv2d_21", 0, 0, {}]]], "name": "max_pooling2d_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)_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_37", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["activation_5", 0, 0, {}]]], "name": "conv2d_37"}
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_38", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_37", 0, 0, {}]]], "name": "conv2d_38"}
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_39", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_37", 0, 0, {}]]], "name": "conv2d_39"}
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_38", 0, 0, {}], ["conv2d_39", 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_40", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["activation_6", 0, 0, {}]]], "name": "conv2d_40"}
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_41", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_40", 0, 0, {}]]], "name": "conv2d_41"}
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_42", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_40", 0, 0, {}]]], "name": "conv2d_42"}
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_41", 0, 0, {}], ["conv2d_42", 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_22", "padding": "same", "strides": [1, 1], "trainable": false, "use_bias": true}, "inbound_nodes": [[["max_pooling2d_13", 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)_layer40{"class_name": "MaxPooling2D", "config": {"data_format": "channels_last", "name": "max_pooling2d_15", "padding": "valid", "pool_size": [2, 2], "strides": [2, 2], "trainable": true}, "inbound_nodes": [[["activation_7", 0, 0, {}]]], "name": "max_pooling2d_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)_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_43", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["max_pooling2d_15", 0, 0, {}]]], "name": "conv2d_43"}
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_44", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_43", 0, 0, {}]]], "name": "conv2d_44"}
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_45", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_43", 0, 0, {}]]], "name": "conv2d_45"}
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_44", 0, 0, {}], ["conv2d_45", 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_9", "noise_shape": null, "rate": 0.5, "seed": null, "trainable": true}, "inbound_nodes": [[["activation_8", 0, 0, {}]]], "name": "dropout_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)_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_46", "padding": "valid", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["dropout_9", 0, 0, {}]]], "name": "conv2d_46"}
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_46", 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_5", "trainable": true}, "inbound_nodes": [[["average_pooling2d_1", 0, 0, {}]]], "name": "flatten_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)_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_23", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_22", 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)_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_13", "trainable": true, "units": 10, "use_bias": true}, "inbound_nodes": [[["flatten_5", 0, 0, {}]]], "name": "dense_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)_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_24", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["conv2d_22", 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)_layer7{"class_name": "Concatenate", "config": {"axis": 1, "name": "concatenate_1", "trainable": true}, "inbound_nodes": [[["conv2d_23", 0, 0, {}], ["conv2d_24", 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_25", "padding": "same", "strides": [1, 1], "trainable": true, "use_bias": true}, "inbound_nodes": [[["activation_1", 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)_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
0.9997 ± 0.0001
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9814 ± 0.0019
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9794 ± 0.0021
Cross-validation details (10-fold Crossvalidation)
KB relative information score
68689.3084 ± 9.6923
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0045 ± 0.0003
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
0.9814 ± 0.0018
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9814 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3198
Cross-validation details (10-fold Crossvalidation)
Recall
0.9814 ± 0.0019
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0248 ± 0.0016
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0543 ± 0.0022
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.1811 ± 0.0075
Cross-validation details (10-fold Crossvalidation)