Run
10457946

Run 10457946

Task 9981 (Supervised Classification) cnae-9 Uploaded 19-05-2020 by Marc Zöller
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  • automl_meta_features openml-python Sklearn_0.22.1.
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Flow

sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._pca.PCA,step_1=skle arn.naive_bayes.BernoulliNB)(1)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 it to 'passthrough' or ``None``.
sklearn.naive_bayes.BernoulliNB(11)_alpha96.80433397149353
sklearn.naive_bayes.BernoulliNB(11)_binarize0.0
sklearn.naive_bayes.BernoulliNB(11)_class_priornull
sklearn.naive_bayes.BernoulliNB(11)_fit_priortrue
sklearn.decomposition._pca.PCA(1)_copyfalse
sklearn.decomposition._pca.PCA(1)_iterated_power52
sklearn.decomposition._pca.PCA(1)_n_components111
sklearn.decomposition._pca.PCA(1)_random_state42
sklearn.decomposition._pca.PCA(1)_svd_solver"randomized"
sklearn.decomposition._pca.PCA(1)_tol3.9097780818058077
sklearn.decomposition._pca.PCA(1)_whitenfalse
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._pca.PCA,step_1=sklearn.naive_bayes.BernoulliNB)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._pca.PCA,step_1=sklearn.naive_bayes.BernoulliNB)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_1", "step_name": "step_1"}}]
sklearn.pipeline.Pipeline(step_0=sklearn.decomposition._pca.PCA,step_1=sklearn.naive_bayes.BernoulliNB)(1)_verbosefalse

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.

18 Evaluation measures

0.9672 ± 0.0129
Per class
Cross-validation details (10-fold Crossvalidation)
0.8076 ± 0.023
Per class
Cross-validation details (10-fold Crossvalidation)
0.7833 ± 0.024
Cross-validation details (10-fold Crossvalidation)
0.6033 ± 0.0205
Cross-validation details (10-fold Crossvalidation)
0.1129 ± 0.0039
Cross-validation details (10-fold Crossvalidation)
0.1975
Cross-validation details (10-fold Crossvalidation)
0.8074 ± 0.0213
Cross-validation details (10-fold Crossvalidation)
1080
Per class
Cross-validation details (10-fold Crossvalidation)
0.8135 ± 0.0228
Per class
Cross-validation details (10-fold Crossvalidation)
0.8074 ± 0.0213
Cross-validation details (10-fold Crossvalidation)
3.1699
Cross-validation details (10-fold Crossvalidation)
0.5714 ± 0.0198
Cross-validation details (10-fold Crossvalidation)
0.3143
Cross-validation details (10-fold Crossvalidation)
0.2065 ± 0.0059
Cross-validation details (10-fold Crossvalidation)
0.6572 ± 0.0188
Cross-validation details (10-fold Crossvalidation)
0.8074 ± 0.0213
Cross-validation details (10-fold Crossvalidation)