Run
9201678

Run 9201678

Task 3573 (Supervised Classification) mnist_784 Uploaded 20-05-2018 by Irfan Nur Afif
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Flow

keras.wrappers.scikit_learn.KerasClassifier(2)Automatically created scikit-learn flow.
keras.wrappers.scikit_learn.KerasClassifier(2)_batch_size128
keras.wrappers.scikit_learn.KerasClassifier(2)_build_fn"def squeezenet_mnist():\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',b"
keras.wrappers.scikit_learn.KerasClassifier(2)_epochs3
keras.wrappers.scikit_learn.KerasClassifier(2)_verbose1

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
0.9986 ± 0.0008
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9625 ± 0.0237
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9582 ± 0.0272
Cross-validation details (10-fold Crossvalidation)
KB relative information score
67211.6524 ± 176.4865
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0101 ± 0.0065
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
0.9629 ± 0.017
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9624 ± 0.0245
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3198
Cross-validation details (10-fold Crossvalidation)
Recall
0.9624 ± 0.0245
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.056 ± 0.0363
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.0766 ± 0.0229
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2553 ± 0.0764
Cross-validation details (10-fold Crossvalidation)