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]