Run
10593654

Run 10593654

Task 1917 (Supervised Classification) diabetes Uploaded 20-04-2023 by ALEJANDRO REYNOSO
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Flow

sklearn.neighbors._classification.KNeighborsClassifier(19)Classifier implementing the k-nearest neighbors vote.
sklearn.neighbors._classification.KNeighborsClassifier(19)_algorithm"auto"
sklearn.neighbors._classification.KNeighborsClassifier(19)_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(19)_metric"minkowski"
sklearn.neighbors._classification.KNeighborsClassifier(19)_metric_paramsnull
sklearn.neighbors._classification.KNeighborsClassifier(19)_n_jobsnull
sklearn.neighbors._classification.KNeighborsClassifier(19)_n_neighbors10
sklearn.neighbors._classification.KNeighborsClassifier(19)_p2
sklearn.neighbors._classification.KNeighborsClassifier(19)_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
0.7801 ± 0.0534
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
F measure
0.7305 ± 0.0442
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Kappa
0.3933 ± 0.1001
Cross-validation details (10 times 10-fold Crossvalidation)
KB relative information score
0.2715 ± 0.064
Cross-validation details (10 times 10-fold Crossvalidation)
Mean absolute error
0.3317 ± 0.0255
Cross-validation details (10 times 10-fold Crossvalidation)
Mean prior absolute error
0.4545 ± 0.001
Cross-validation details (10 times 10-fold Crossvalidation)
Weighted recall
0.7438 ± 0.0401
Cross-validation details (10 times 10-fold Crossvalidation)
Number of instances
7680
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Precision
0.7363 ± 0.0463
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
Predictive accuracy
0.7438 ± 0.0401
Cross-validation details (10 times 10-fold Crossvalidation)
Prior entropy
0.9331 ± 0.0031
Cross-validation details (10 times 10-fold Crossvalidation)
Relative absolute error
0.7298 ± 0.0559
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean prior squared error
0.4766 ± 0.0011
Cross-validation details (10 times 10-fold Crossvalidation)
Root mean squared error
0.4211 ± 0.0274
Cross-validation details (10 times 10-fold Crossvalidation)
Root relative squared error
0.8836 ± 0.0573
Cross-validation details (10 times 10-fold Crossvalidation)
Unweighted recall
0.6828 ± 0.0493
Cross-validation details (10 times 10-fold Crossvalidation)