Run
10594054

Run 10594054

Task 9983 (Supervised Classification) eeg-eye-state Uploaded 09-08-2023 by Nuttapong Chimwai
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Flow

sklearn.neighbors._classification.KNeighborsClassifier(21)Classifier implementing the k-nearest neighbors vote.
sklearn.neighbors._classification.KNeighborsClassifier(21)_algorithm"auto"
sklearn.neighbors._classification.KNeighborsClassifier(21)_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(21)_metric"minkowski"
sklearn.neighbors._classification.KNeighborsClassifier(21)_metric_paramsnull
sklearn.neighbors._classification.KNeighborsClassifier(21)_n_jobsnull
sklearn.neighbors._classification.KNeighborsClassifier(21)_n_neighbors3
sklearn.neighbors._classification.KNeighborsClassifier(21)_p2
sklearn.neighbors._classification.KNeighborsClassifier(21)_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
0.9931 ± 0.0019
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9747 ± 0.0041
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9489 ± 0.0083
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.9177 ± 0.0057
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0428 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4948 ± 0
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.9747 ± 0.0041
Cross-validation details (10-fold Crossvalidation)
Number of instances
14980
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9747 ± 0.0041
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9747 ± 0.0041
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9924 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0865 ± 0.0055
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4974 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1478 ± 0.0074
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.2972 ± 0.0148
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.9744 ± 0.0043
Cross-validation details (10-fold Crossvalidation)