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Hugo Spee
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Hugo's flows

sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis,outlierCLF=sklearn.ensemble.iforest.IsolationForest)) (1)
Automatically created scikit-learn flow.
10 runs0 likes0 downloads0 reach0 impact
scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis,outlierCLF=sklearn.ensemble.iforest.IsolationForest) (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
60 runs0 likes0 downloads0 reach0 impact
sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.neighbors.classification.KNeighborsClassifier,outlierCLF=sklearn.ensemble.iforest.IsolationForest)) (1)
Automatically created scikit-learn flow.
37 runs0 likes0 downloads0 reach0 impact
scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.neighbors.classification.KNeighborsClassifier,outlierCLF=sklearn.ensemble.iforest.IsolationForest) (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.svm.classes.SVC,outlierCLF=sklearn.ensemble.iforest.IsolationForest)) (1)
Automatically created scikit-learn flow.
37 runs0 likes0 downloads0 reach0 impact
scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.svm.classes.SVC,outlierCLF=sklearn.ensemble.iforest.IsolationForest) (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.ensemble.forest.RandomForestClassifier,outlierCLF=sklearn.ensemble.iforest.IsolationForest)) (1)
Automatically created scikit-learn flow.
37 runs0 likes0 downloads0 reach0 impact
scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.ensemble.forest.RandomForestClassifier,outlierCLF=sklearn.ensemble.iforest.IsolationForest) (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.naive_bayes.MultinomialNB,outlierCLF=sklearn.ensemble.iforest.IsolationForest)) (1)
Automatically created scikit-learn flow.
38 runs0 likes0 downloads0 reach0 impact
scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.naive_bayes.MultinomialNB,outlierCLF=sklearn.ensemble.iforest.IsolationForest) (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.tree.tree.DecisionTreeClassifier,outlierCLF=sklearn.ensemble.iforest.IsolationForest)) (1)
Automatically created scikit-learn flow.
38 runs0 likes0 downloads0 reach0 impact
scripts.machineLearningAlgorithms.WithoutOutliersClassifier(classifier=sklearn.tree.tree.DecisionTreeClassifier,outlierCLF=sklearn.ensemble.iforest.IsolationForest) (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.iforest.IsolationForest (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.ExtraTreeClassifier) (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.neighbors.classification.KNeighborsClassifier) (1)
Automatically created scikit-learn flow.
8 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
223 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
231 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.naive_bayes.MultinomialNB) (1)
Automatically created scikit-learn flow.
9 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier) (1)
Automatically created scikit-learn flow.
242 runs0 likes0 downloads0 reach0 impact
sklearn.impute.SimpleImputer (5)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.neighbors.classification.KNeighborsClassifier) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.neighbors.classification.KNeighborsClassifier (32)
Automatically created scikit-learn flow.
7 runs0 likes0 downloads0 reach7 impact
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.svm.classes.SVC) (4)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.svm.classes.SVC (23)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.ensemble.forest.RandomForestClassifier) (4)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.forest.RandomForestClassifier (46)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.naive_bayes.MultinomialNB) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.naive_bayes.MultinomialNB (4)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.naive_bayes.MultinomialNB (3)
Automatically created scikit-learn flow.
4 runs0 likes0 downloads0 reach0 impact
weka.LogitBoost_Bagging_IBk (1)
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
2 runs0 likes1 downloads1 reach0 impact
weka.Bagging_IBk (3)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
175 runs0 likes0 downloads0 reach175 impact
weka.LogitBoost_Bagging_RandomForest (1)
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
1 runs0 likes1 downloads1 reach0 impact
weka.Bagging_RandomForest (10)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.MultiClassClassifier_LogitBoost_Bagging_REPTree (1)
Weka implementation of MultiClassClassifier
1 runs0 likes2 downloads2 reach0 impact
weka.LogitBoost_Bagging_REPTree (3)
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
3 runs0 likes1 downloads1 reach0 impact
weka.Bagging_REPTree (21)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_RandomCommittee_RandomTree (1)
Weka implementation of CostSensitiveClassifier
1 runs0 likes1 downloads1 reach0 impact
weka.CostSensitiveClassifier_Vote_ZeroR (1)
Weka implementation of CostSensitiveClassifier
1 runs0 likes1 downloads1 reach0 impact
weka.NaiveBayesMultinomial (3)
Andrew Mccallum, Kamal Nigam: A Comparison of Event Models for Naive Bayes Text Classification. In: AAAI-98 Workshop on 'Learning for Text Categorization', 1998.
1 runs0 likes1 downloads1 reach0 impact