Run
10587703

Run 10587703

Task 3 (Supervised Classification) kr-vs-kp Uploaded 10-02-2022 by Quan Deng
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Flow

sklearn.pipeline.Pipeline(encoder=sklearn.preprocessing._encoders.OrdinalEn coder,clf=sklearn.tree._classes.DecisionTreeClassifier)(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.tree._classes.DecisionTreeClassifier(23)_ccp_alpha0.0
sklearn.tree._classes.DecisionTreeClassifier(23)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(23)_criterion"gini"
sklearn.tree._classes.DecisionTreeClassifier(23)_max_depthnull
sklearn.tree._classes.DecisionTreeClassifier(23)_max_featuresnull
sklearn.tree._classes.DecisionTreeClassifier(23)_max_leaf_nodesnull
sklearn.tree._classes.DecisionTreeClassifier(23)_min_impurity_decrease0.0
sklearn.tree._classes.DecisionTreeClassifier(23)_min_samples_leaf1
sklearn.tree._classes.DecisionTreeClassifier(23)_min_samples_split2
sklearn.tree._classes.DecisionTreeClassifier(23)_min_weight_fraction_leaf0.0
sklearn.tree._classes.DecisionTreeClassifier(23)_random_state43003
sklearn.tree._classes.DecisionTreeClassifier(23)_splitter"best"
sklearn.pipeline.Pipeline(encoder=sklearn.preprocessing._encoders.OrdinalEncoder,clf=sklearn.tree._classes.DecisionTreeClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(encoder=sklearn.preprocessing._encoders.OrdinalEncoder,clf=sklearn.tree._classes.DecisionTreeClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "encoder", "step_name": "encoder"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "clf", "step_name": "clf"}}]
sklearn.pipeline.Pipeline(encoder=sklearn.preprocessing._encoders.OrdinalEncoder,clf=sklearn.tree._classes.DecisionTreeClassifier)(1)_verbosefalse
sklearn.preprocessing._encoders.OrdinalEncoder(4)_categories"auto"
sklearn.preprocessing._encoders.OrdinalEncoder(4)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OrdinalEncoder(4)_handle_unknown"use_encoded_value"
sklearn.preprocessing._encoders.OrdinalEncoder(4)_unknown_value-1

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

0.9956 ± 0.0037
Per class
Cross-validation details (10-fold Crossvalidation)
0.9956 ± 0.0037
Per class
Cross-validation details (10-fold Crossvalidation)
0.9912 ± 0.0074
Cross-validation details (10-fold Crossvalidation)
0.9912 ± 0.0074
Cross-validation details (10-fold Crossvalidation)
0.0044 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
0.499 ± 0
Cross-validation details (10-fold Crossvalidation)
0.9956 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
3196
Per class
Cross-validation details (10-fold Crossvalidation)
0.9956 ± 0.0036
Per class
Cross-validation details (10-fold Crossvalidation)
0.9956 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
0.9986 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.0088 ± 0.0074
Cross-validation details (10-fold Crossvalidation)
0.4995 ± 0
Cross-validation details (10-fold Crossvalidation)
0.0662 ± 0.0399
Cross-validation details (10-fold Crossvalidation)
0.1325 ± 0.0799
Cross-validation details (10-fold Crossvalidation)
0.9956 ± 0.0037
Cross-validation details (10-fold Crossvalidation)