Run
9201685

Run 9201685

Task 167133 (Supervised Classification) CIFAR_10_small Uploaded 21-05-2018 by Irfan Nur Afif
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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_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)_epochs5
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
0.7627 ± 0.0175
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.2718 ± 0.0194
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.2021 ± 0.0292
Cross-validation details (10-fold Crossvalidation)
KB relative information score
4623.6201 ± 44.7721
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1625 ± 0.003
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
20000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.2747 ± 0.0498
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.2821 ± 0.026
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3218
Cross-validation details (10-fold Crossvalidation)
Recall
0.2821 ± 0.026
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9025 ± 0.0169
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2853 ± 0.0028
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9511 ± 0.0092
Cross-validation details (10-fold Crossvalidation)