10464839 9186 Prabhant Singh 189908 Supervised Classification 18580 keras.engine.sequential.Sequential.9d05377e(1) 8275512 backend "tensorflow" 18580 class_name "Sequential" 18580 config {"name": "sequential_1"} 18580 keras_version "2.2.4" 18580 layer0_batch_normalization_1 {"class_name": "BatchNormalization", "config": {"axis": -1, "beta_constraint": null, "beta_initializer": {"class_name": "Zeros", "config": {}}, "beta_regularizer": null, "center": true, "epsilon": 0.001, "gamma_constraint": null, "gamma_initializer": {"class_name": "Ones", "config": {}}, "gamma_regularizer": null, "momentum": 0.99, "moving_mean_initializer": {"class_name": "Zeros", "config": {}}, "moving_variance_initializer": {"class_name": "Ones", "config": {}}, "name": "batch_normalization_1", "scale": true, "trainable": true}} 18580 layer1_dense_1 {"class_name": "Dense", "config": {"activation": "relu", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "name": "dense_1", "trainable": true, "units": 1024, "use_bias": true}} 18580 layer2_dropout_1 {"class_name": "Dropout", "config": {"name": "dropout_1", "noise_shape": null, "rate": 0.4, "seed": null, "trainable": true}} 18580 layer3_dense_2 {"class_name": "Dense", "config": {"activation": "softmax", "activity_regularizer": null, "bias_constraint": null, "bias_initializer": {"class_name": "Zeros", "config": {}}, "bias_regularizer": null, "kernel_constraint": null, "kernel_initializer": {"class_name": "VarianceScaling", "config": {"distribution": "uniform", "mode": "fan_avg", "scale": 1.0, "seed": null}}, "kernel_regularizer": null, "name": "dense_2", "trainable": true, "units": 10, "use_bias": true}} 18580 optimizer {"loss": "sparse_categorical_crossentropy", "loss_weights": null, "metrics": ["accuracy"], "optimizer_config": {"class_name": "Adam", "config": {"amsgrad": false, "beta_1": 0.8999999761581421, "beta_2": 0.9990000128746033, "decay": 0.0, "epsilon": 1e-07, "lr": 0.0010000000474974513}}, "sample_weight_mode": null, "weighted_metrics": null} 18580 Keras_2.2.4. openml-python 40996 Fashion-MNIST https://www.openml.org/data/download/18238735/phpnBqZGZ -1 21854391 description https://api.openml.org/data/download/21854391/description.xml -1 21854392 predictions https://api.openml.org/data/download/21854392/predictions.arff area_under_roc_curve 0.9874430857270294 [0.98378,0.999,0.979124,0.993534,0.981256,0.994217,0.952837,0.996007,0.994194,0.997986] average_cost 0 f_measure 0.858777122852339 [0.805901,0.981508,0.786371,0.873709,0.778443,0.923402,0.634472,0.908281,0.943218,0.930406] kappa 0.845398704863224 kb_relative_information_score 0.8564880441604167 mean_absolute_error 0.03696699579300854 mean_prior_absolute_error 0.17999999999993396 weighted_recall 0.8608658008658009 [0.85281,0.974825,0.83083,0.934596,0.745223,0.916037,0.560091,0.883499,0.919766,0.972294] number_of_instances 23100 [2242,2423,2264,2217,2355,2382,2205,2309,2393,2310] precision 0.8614494418844204 [0.763883,0.988285,0.746429,0.820269,0.814763,0.930887,0.731635,0.934494,0.967898,0.891978] predictive_accuracy 0.8608658008658009 prior_entropy 3.3219280948880168 relative_absolute_error 0.2053721988501228 root_mean_prior_squared_error 0.299999999999945 root_mean_squared_error 0.14288679111800298 root_relative_squared_error 0.476289303726764 total_cost 0 unweighted_recall 0.8589971562098073 [0.85281,0.974825,0.83083,0.934596,0.745223,0.916037,0.560091,0.883499,0.919766,0.972294] area_under_roc_curve 0.9874430857270294 [0.98378,0.999,0.979124,0.993534,0.981256,0.994217,0.952837,0.996007,0.994194,0.997986] average_cost 0 f_measure 0.858777122852339 [0.805901,0.981508,0.786371,0.873709,0.778443,0.923402,0.634472,0.908281,0.943218,0.930406] kappa 0.845398704863224 kb_relative_information_score 0.8564880441604167 mean_absolute_error 0.03696699579300854 mean_prior_absolute_error 0.17999999999993396 weighted_recall 0.8608658008658009 [0.85281,0.974825,0.83083,0.934596,0.745223,0.916037,0.560091,0.883499,0.919766,0.972294] number_of_instances 23100 [2242,2423,2264,2217,2355,2382,2205,2309,2393,2310] precision 0.8614494418844204 [0.763883,0.988285,0.746429,0.820269,0.814763,0.930887,0.731635,0.934494,0.967898,0.891978] predictive_accuracy 0.8608658008658009 prior_entropy 3.3219280948880168 relative_absolute_error 0.2053721988501228 root_mean_prior_squared_error 0.299999999999945 root_mean_squared_error 0.14288679111800298 root_relative_squared_error 0.476289303726764 total_cost 0 unweighted_recall 0.8589971562098073 [0.85281,0.974825,0.83083,0.934596,0.745223,0.916037,0.560091,0.883499,0.919766,0.972294]