Run
10595198

Run 10595198

Task 59 (Supervised Classification) iris Uploaded 18-12-2024 by Subhaditya Mukherjee
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Flow

sklearn.neighbors._classification.KNeighborsClassifier(25)Classifier implementing the k-nearest neighbors vote.
sklearn.neighbors._classification.KNeighborsClassifier(25)_algorithm"auto"
sklearn.neighbors._classification.KNeighborsClassifier(25)_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(25)_metric"minkowski"
sklearn.neighbors._classification.KNeighborsClassifier(25)_metric_paramsnull
sklearn.neighbors._classification.KNeighborsClassifier(25)_n_jobsnull
sklearn.neighbors._classification.KNeighborsClassifier(25)_n_neighbors10
sklearn.neighbors._classification.KNeighborsClassifier(25)_p2
sklearn.neighbors._classification.KNeighborsClassifier(25)_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.

html
Report html

18 Evaluation measures

Area under ROC curve
0.9971 ± 0.0085
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9667 ± 0.0355
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.95 ± 0.0527
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.9257 ± 0.0441
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0413 ± 0.0231
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4444
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.9667 ± 0.0351
Cross-validation details (10-fold Crossvalidation)
Number of instances
150
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9668 ± 0.0293
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9667 ± 0.0351
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.585
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.093 ± 0.0519
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4714
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1332 ± 0.0502
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2825 ± 0.1066
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.9667 ± 0.0351
Cross-validation details (10-fold Crossvalidation)