| 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 | 5 |
| keras.wrappers.scikit_learn.KerasClassifier(2)_verbose | 1 |
0.9851 ± 0.0015 Per class Cross-validation details (10-fold Crossvalidation)
|
0.8448 ± 0.0233 Per class Cross-validation details (10-fold Crossvalidation)
|
0.8288 ± 0.0256 Cross-validation details (10-fold Crossvalidation)
|
59359.9064 ± 143.1082 Cross-validation details (10-fold Crossvalidation)
|
0.0381 ± 0.0053 Cross-validation details (10-fold Crossvalidation)
|
0.18 Cross-validation details (10-fold Crossvalidation)
|
70000 Per class Cross-validation details (10-fold Crossvalidation) |
0.8448 ± 0.0113 Per class Cross-validation details (10-fold Crossvalidation)
|
0.846 ± 0.023 Cross-validation details (10-fold Crossvalidation)
|
3.3219 Cross-validation details (10-fold Crossvalidation)
|
0.846 ± 0.023 Per class Cross-validation details (10-fold Crossvalidation)
|
0.2118 ± 0.0294 Cross-validation details (10-fold Crossvalidation)
|
0.3 Cross-validation details (10-fold Crossvalidation)
|
0.1488 ± 0.0102 Cross-validation details (10-fold Crossvalidation)
|
0.496 ± 0.0339 Cross-validation details (10-fold Crossvalidation)
|