Package smile.validation

Model validation.

See: Description

Interface Summary

Interface	Description
ClassificationMeasure	An abstract interface to measure the classification performance.
ClusterMeasure	An abstract interface to measure the clustering performance.
RegressionMeasure	An abstract interface to measure the regression performance.

Class Summary

Class	Description
Accuracy	The accuracy is the proportion of true results (both true positives and true negatives) in the population.
AccuracyTest
AdjustedRandIndex	Adjusted Rand Index.
AdjustedRandIndexTest
AUC	The area under the curve (AUC).
Bootstrap	The bootstrap is a general tool for assessing statistical accuracy.
BootstrapTest
ConfusionMatrix	Generates the confusion matrix based on truth and prediction vectors
ConfusionMatrixTest
CrossValidation	Cross-validation is a technique for assessing how the results of a statistical analysis will generalize to an independent data set.
CrossValidationTest
Fallout	Fall-out, false alarm rate, or false positive rate (FPR)
FalloutTest
FDR	The false discovery rate (FDR) is ratio of false positives to combined true and false positives, which is actually 1 - precision.
FDRTest
FMeasure	The F-score (or F-measure) considers both the precision and the recall of the test to compute the score.
FMeasureTest
LOOCV	Leave-one-out cross validation.
LOOCVTest
MeanAbsoluteDeviation	Mean absolute deviation error.
MSE	Mean squared error.
MSETest
Precision	The precision or positive predictive value (PPV) is ratio of true positives to combined true and false positives, which is different from sensitivity.
PrecisionTest
RandIndex	Rand Index.
RandIndexTest
Recall	In information retrieval area, sensitivity is called recall.
RecallTest
RMSE	Root mean squared error.
RMSETest
RSS	Residual sum of squares.
RSSTest
Sensitivity	Sensitivity or true positive rate (TPR) (also called hit rate, recall) is a statistical measures of the performance of a binary classification test.
SensitivityTest
Specificity	Specificity (SPC) or True Negative Rate is a statistical measures of the performance of a binary classification test.
SpecificityTest
Validation	A utility class for validating predictive models on test data.
ValidationTest

Package smile.validation Description

Model validation.