Run
10437797

Run 10437797

Task 2274 (Supervised Classification) meta_ensembles.arff Uploaded 03-03-2020 by Fares Gaaloul
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Flow

sklearn.pipeline.Pipeline(featureagglomeration=sklearn.cluster.hierarchical .FeatureAgglomeration,decisiontreeclassifier=sklearn.tree.tree.DecisionTree Classifier)(2)Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit and transform methods. The final estimator only needs to implement fit. The transformers in the pipeline can be cached using ``memory`` argument. The purpose of the pipeline is to assemble several steps that can be cross-validated together while setting different parameters. For this, it enables setting parameters of the various steps using their names and the parameter name separated by a '__', as in the example below. A step's estimator may be replaced entirely by setting the parameter with its name to another estimator, or a transformer removed by setting to None.
sklearn.pipeline.Pipeline(featureagglomeration=sklearn.cluster.hierarchical.FeatureAgglomeration,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(2)_memorynull
sklearn.pipeline.Pipeline(featureagglomeration=sklearn.cluster.hierarchical.FeatureAgglomeration,decisiontreeclassifier=sklearn.tree.tree.DecisionTreeClassifier)(2)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "featureagglomeration", "step_name": "featureagglomeration"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "decisiontreeclassifier", "step_name": "decisiontreeclassifier"}}]
sklearn.cluster.hierarchical.FeatureAgglomeration(4)_affinity"manhattan"
sklearn.cluster.hierarchical.FeatureAgglomeration(4)_compute_full_tree"auto"
sklearn.cluster.hierarchical.FeatureAgglomeration(4)_connectivitynull
sklearn.cluster.hierarchical.FeatureAgglomeration(4)_linkage"average"
sklearn.cluster.hierarchical.FeatureAgglomeration(4)_memorynull
sklearn.cluster.hierarchical.FeatureAgglomeration(4)_n_clusters2
sklearn.cluster.hierarchical.FeatureAgglomeration(4)_pooling_func{"oml-python:serialized_object": "function", "value": "numpy.mean"}
sklearn.tree.tree.DecisionTreeClassifier(64)_class_weightnull
sklearn.tree.tree.DecisionTreeClassifier(64)_criterion"gini"
sklearn.tree.tree.DecisionTreeClassifier(64)_max_depth10
sklearn.tree.tree.DecisionTreeClassifier(64)_max_featuresnull
sklearn.tree.tree.DecisionTreeClassifier(64)_max_leaf_nodesnull
sklearn.tree.tree.DecisionTreeClassifier(64)_min_impurity_decrease0.0
sklearn.tree.tree.DecisionTreeClassifier(64)_min_impurity_splitnull
sklearn.tree.tree.DecisionTreeClassifier(64)_min_samples_leaf13
sklearn.tree.tree.DecisionTreeClassifier(64)_min_samples_split16
sklearn.tree.tree.DecisionTreeClassifier(64)_min_weight_fraction_leaf0.0
sklearn.tree.tree.DecisionTreeClassifier(64)_presortfalse
sklearn.tree.tree.DecisionTreeClassifier(64)_random_state22408
sklearn.tree.tree.DecisionTreeClassifier(64)_splitter"best"

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.

16 Evaluation measures

0.45 ± 0.2018
Per class
Cross-validation details (10-fold Crossvalidation)
0.022
0.0619 ± 0.1038
Cross-validation details (10-fold Crossvalidation)
0.2893 ± 0.0319
Cross-validation details (10-fold Crossvalidation)
0.2904 ± 0.025
Cross-validation details (10-fold Crossvalidation)
0.5946 ± 0.1277
Cross-validation details (10-fold Crossvalidation)
74
Per class
Cross-validation details (10-fold Crossvalidation)
0.5946 ± 0.1277
Cross-validation details (10-fold Crossvalidation)
1.5452 ± 0.2578
Cross-validation details (10-fold Crossvalidation)
0.9963 ± 0.0789
Cross-validation details (10-fold Crossvalidation)
0.3782 ± 0.0332
Cross-validation details (10-fold Crossvalidation)
0.404 ± 0.0432
Cross-validation details (10-fold Crossvalidation)
1.0682 ± 0.0671
Cross-validation details (10-fold Crossvalidation)
0.2567
Cross-validation details (10-fold Crossvalidation)