| Issue | #Downvotes for this reason | By |
|---|
| keras.wrappers.scikit_learn.KerasClassifier(2) | Automatically created scikit-learn flow. |
| keras.wrappers.scikit_learn.KerasClassifier(2)_batch_size | 32 |
| keras.wrappers.scikit_learn.KerasClassifier(2)_build_fn | "def squeezenet_cifar10():\n input_layer = Input(shape=(3072,), name=\"input\")\n reshape_layer=Reshape((32, 32,3))(input_layer)\n conv1 = Convolution2D(96, 3, 3, activation='relu', init='glorot_uniform',subsample=(2,2),border_mode='valid')(reshape_layer)\n maxpool1 = MaxPooling2D(pool_size=(2,2))(conv1)\n fire2_squeeze = Convolution2D(16, 1, 1, activation='relu', init='glorot_uniform',border_mode='same')(maxpool1)\n fire2_expand1 = Convolution2D(64, 1, 1, activation='relu', init='glorot_uniform',border_mode='same')(fire2_squeeze)\n fire2_expand2 = Convolution2D(64, 3, 3, activation='relu', init='glorot_uniform',border_mode='same')(fire2_squeeze)\n merge1 = merge(inputs=[fire2_expand1, fire2_expand2], mode=\"concat\", concat_axis=1)\n fire2 = Activation(\"linear\")(merge1)\n fire3_squeeze = Convolution2D(16, 1, 1, activation='relu', init='glorot_uniform',border_mode='same')(fire2)\n fire3_expand1 = Convolution2D(64, 1, 1, activation='relu', init='glorot_uniform',border_mode='same')(fire3_squeeze)\n fire3_expand2 = Convolution2D(64, 3, 3, activation='relu', init='glorot_uniform',border_mode='same')(fire3_squeeze)\n merge2 = merge(inputs=[fire3_expand1, fire3_expand2], mode=\"concat\", concat_axis=1)\n fire3 = Activation(\"linear\")(merge2)\n fire4_squeeze = Convolution2D(32, 1, 1, activation='relu', init='glorot_uniform',border_mode='same')(fire3)\n fire4_expand1 = Convolution2D(128, 1, 1, activation='relu', init='glorot_uniform',border_mode='same')(fire4_squeeze)\n fire4_expand2 = Convolution2D(128, 3, 3, activation='relu', init='glorot_uniform',border_mode='same')(fire4_squeeze)\n merge3 = merge(inputs=[fire4_expand1, fire4_expand2], mode=\"concat\", concat_axis=1)\n fire4 = Activation(\"linear\")(merge3)\n maxpool4 = MaxPooling2D((2,2))(fire4)\n fire5_squeeze = Convolution2D(32, 1, 1, activation='relu', init='glorot_uniform',border_mode='same')(maxpool4)\n fire5_expand1 = Convolution2D(128, 1, 1, activation='relu', init='glorot_uniform" |
| keras.wrappers.scikit_learn.KerasClassifier(2)_epochs | 5 |
| keras.wrappers.scikit_learn.KerasClassifier(2)_verbose | 1 |
0.8144 ± 0.0059 Per class Cross-validation details (10-fold Crossvalidation)
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0.3589 ± 0.0221 Per class Cross-validation details (10-fold Crossvalidation)
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0.2926 ± 0.0296 Cross-validation details (10-fold Crossvalidation)
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6466.9205 ± 39.4822 Cross-validation details (10-fold Crossvalidation)
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0.15 ± 0.004 Cross-validation details (10-fold Crossvalidation)
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0.18 ± 0 Cross-validation details (10-fold Crossvalidation)
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20000 Per class Cross-validation details (10-fold Crossvalidation) |
0.3626 ± 0.0284 Per class Cross-validation details (10-fold Crossvalidation)
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0.3634 ± 0.0266 Cross-validation details (10-fold Crossvalidation)
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3.3218 Cross-validation details (10-fold Crossvalidation)
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0.3634 ± 0.0266 Per class Cross-validation details (10-fold Crossvalidation)
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0.8336 ± 0.0221 Cross-validation details (10-fold Crossvalidation)
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0.3 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.2758 ± 0.0029 Cross-validation details (10-fold Crossvalidation)
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0.9192 ± 0.0095 Cross-validation details (10-fold Crossvalidation)
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