Run
10591695

Run 10591695

Task 10101 (Supervised Classification) blood-transfusion-service-center Uploaded 15-11-2022 by Laurens Krudde
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Flow

sklearn.neighbors._classification.KNeighborsClassifier(15)Classifier implementing the k-nearest neighbors vote.
sklearn.neighbors._classification.KNeighborsClassifier(15)_algorithm"auto"
sklearn.neighbors._classification.KNeighborsClassifier(15)_leaf_size30
`_ and the metrics listed in :class:`~sklearn.metrics.pairwise.distance_metrics` for valid metric values If metric is "precomputed", X is assumed to be a distance matrix and must be square during fit. X may be a :term:`sparse graph`, in which case only "nonzero" elements may be considered neighbors If metric is a callable function, it takes two arrays representing 1D vectors as inputs and must return one value indicating the distance between those vectors. This works for Scipy's metrics, but is less efficient than passing the metric name as a string">sklearn.neighbors._classification.KNeighborsClassifier(15)_metric"minkowski"
sklearn.neighbors._classification.KNeighborsClassifier(15)_metric_paramsnull
sklearn.neighbors._classification.KNeighborsClassifier(15)_n_jobsnull
sklearn.neighbors._classification.KNeighborsClassifier(15)_n_neighbors3
sklearn.neighbors._classification.KNeighborsClassifier(15)_p2
sklearn.neighbors._classification.KNeighborsClassifier(15)_weights"uniform"

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

Area under ROC curve
0.6578 ± 0.0572
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7135 ± 0.0616
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.199 ± 0.1523
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.0032 ± 0.1193
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3128 ± 0.036
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.363 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.7179 ± 0.0693
Cross-validation details (10-fold Crossvalidation)
Number of instances
748
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7097 ± 0.0627
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7179 ± 0.0693
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.7916 ± 0.0072
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8617 ± 0.0982
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4258 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4554 ± 0.0354
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0694 ± 0.0831
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.5966 ± 0.0688
Cross-validation details (10-fold Crossvalidation)