smplmark

OpenML-CC18: Fashion-MNIST

Best predictive accuracy per machine-learning flow on the Fashion-MNIST classification task from the OpenML-CC18 suite.

Community results for the Fashion-MNIST classification task from OpenML-CC18, OpenML's curated suite of 72 classification tasks (www.openml.org/t/146825). Each target is a flow — a specific algorithm or pipeline — shown with the best predictive accuracy recorded for it on this task in OpenML's public evaluation listing, under the task's fixed estimation procedure.

Metrics

  • predictive_accuracy

Targets (50)

  • automlbenchmark_autosklearn(1)
  • automlbenchmark_autoweka(1)
  • automlbenchmark_h2oautoml(1)
  • automlbenchmark_randomforest(1)
  • automlbenchmark_tpot(1)
  • automlbenchmark_tunedrandomforest(1)
  • keras.engine.sequential.Sequential.5F750FE4F9E4AAE0(1)
  • keras.wrappers.scikit_learn.KerasClassifier(2)
  • keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concatenate,Activation,Conv2D,Conv2D,Conv2D,Concate…
  • keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Conv2D,Conv2D,Conv2D,Merge,Activation,Conv2D,Conv2D,Conv2D,Merge,Activation,Conv2D,Conv2D,Conv2D,Merge,Activation,Ma…
  • keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Reshape,ZeroPadding2D,Conv2D,Conv2D,BatchNormalization,Activation,Conv2D,BatchNormalization,Activation,Conv2D,Conv2D,Add,BatchNormalizat…
  • keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,ZeroPadding2D,Conv2D,Conv2D,BatchNormalization,Activation,Conv2D,BatchNormalization,Add,Activation,Conv2D,BatchNormalization,Activation,…
  • keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,ZeroPadding2D,Conv2D,Conv2D,BatchNormalization,Activation,Conv2D,BatchNormalization,Add,Activation,Conv2D,BatchNormalization,Activation,…
  • keras.wrappers.scikit_learn.KerasClassifier(Reshape,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Fl…
  • keras.wrappers.scikit_learn.KerasClassifier(Reshape,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Fl…
  • keras.wrappers.scikit_learn.KerasClassifier(Reshape,Conv2D,MaxPooling2D,Activation,Conv2D,MaxPooling2D,Activation,Dropout,Conv2D,Flatten,Dense,Activation,Dense,Activation)(3)
  • keras.wrappers.scikit_learn.KerasClassifier(Reshape,Conv2D,MaxPooling2D,Activation,Conv2D,MaxPooling2D,Activation,Dropout,Conv2D,Flatten,Dense,Activation,Dense,Activation)(5)
  • keras.wrappers.scikit_learn.KerasClassifier(Reshape,Conv2D,MaxPooling2D,Activation,Conv2D,MaxPooling2D,Activation,Dropout,Conv2D,Flatten,Dense,Activation,Dense,Activation)(2)
  • keras.wrappers.scikit_learn.KerasClassifier(Reshape,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Flatten,Dense,Dr…
  • sklearn.discriminant_analysis.LinearDiscriminantAnalysis(2)
  • sklearn.ensemble.forest.RandomForestClassifier(32)
  • sklearn.ensemble.forest.RandomForestClassifier(35)
  • sklearn.ensemble.forest.RandomForestClassifier(57)
  • sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(22)
  • sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(6)
  • sklearn.linear_model._logistic.LogisticRegression(1)
  • sklearn.linear_model._logistic.LogisticRegression(2)
  • sklearn.linear_model.logistic.LogisticRegression(29)
  • sklearn.linear_model.logistic.LogisticRegression(30)
  • sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)
  • sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)
  • sklearn.neighbors.classification.KNeighborsClassifier(25)
  • sklearn.neighbors.classification.KNeighborsClassifier(34)
  • sklearn.neural_network.multilayer_perceptron.MLPClassifier(16)
  • sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_thresho…
  • sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethre…
  • sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold…
  • sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,encoder=sklearn.preprocessing._encoders.OneHotEncoder,model=sklearn.tree._classes.DecisionTreeClassifier)(2)
  • sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(1)
  • sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier)(2)
  • sklearn.pipeline.Pipeline(scale=sklearn.preprocessing.data.StandardScaler,SVC=sklearn.svm.classes.LinearSVC)(1)
  • sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,clf=sklearn.tree._classes.DecisionTreeClassifier)(1)
  • sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)
  • sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkceigenpro=sklearn_extra.fast_kernel.FKCEigenPro)(1)
  • sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkc_eigenpro=sklearn_extra.fast_kernel.FKC_EigenPro)(1)
  • sklearn.tree.tree.DecisionTreeClassifier(22)
  • sklearn.tree.tree.ExtraTreeClassifier(23)
  • sklearn.tree.tree.ExtraTreeClassifier(26)
  • sklearn.tree.tree.ExtraTreeClassifier(27)
  • torch.nn.modules.container.Sequential.8a53697fda1551c2(1)

Published by OpenML.