| 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 | 128 |
| keras.wrappers.scikit_learn.KerasClassifier(2)_build_fn | "def squeezenet_fmnist():\n input_layer = Input(shape=(784,), name=\"input\")\n reshape_layer=Reshape((28, 28,1))(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 | 3 |
| keras.wrappers.scikit_learn.KerasClassifier(2)_verbose | 1 |
0.9824 ± 0.0024 Per class Cross-validation details (10-fold Crossvalidation)
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0.8306 ± 0.0414 Per class Cross-validation details (10-fold Crossvalidation)
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0.8113 ± 0.0433 Cross-validation details (10-fold Crossvalidation)
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57713.4792 ± 231.0045 Cross-validation details (10-fold Crossvalidation)
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0.0456 ± 0.0082 Cross-validation details (10-fold Crossvalidation)
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0.18 Cross-validation details (10-fold Crossvalidation)
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70000 Per class Cross-validation details (10-fold Crossvalidation) |
0.8324 ± 0.0226 Per class Cross-validation details (10-fold Crossvalidation)
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0.8302 ± 0.039 Cross-validation details (10-fold Crossvalidation)
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3.3219 Cross-validation details (10-fold Crossvalidation)
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0.8302 ± 0.039 Per class Cross-validation details (10-fold Crossvalidation)
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0.2533 ± 0.0456 Cross-validation details (10-fold Crossvalidation)
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0.3 Cross-validation details (10-fold Crossvalidation)
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0.1557 ± 0.0157 Cross-validation details (10-fold Crossvalidation)
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0.519 ± 0.0523 Cross-validation details (10-fold Crossvalidation)
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