logo leastMedSquared

Implements a least median squared linear regression utilizing the existing weka LinearRegression class to form predictions. Least squared regression functions are generated from random subsamples of the data. The least squared regression with the lowest meadian squared error is chosen as the final model. The basis of the algorithm is Peter J. Rousseeuw, Annick M. Leroy (1987). Robust regression and outlier detection.

homepage: weka.sourceforge.net/doc.packages/leastMedSquared
fresh index:
last release: 5 years ago, first release: 5 years ago
packaging: jar
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