Fast Correlation-Based Filter (FCBF)

FCBF is a multivariate feature selection method where the class relevance and the dependency between each feature pair are taken into account. Based on information theory, FCBF uses symmetrical uncertainty to calculate dependencies of features and the class relevance. Starting with the full feature set, FCBF heuristically applies a backward selection technique with a sequential search strategy to remove irrelevant and redundant features. The algorithm stops when there are no features left to eliminate.

Status

Use

val fcbf = FCBFTransformer()
           .setThreshold(.05)

fcbf.fit(dataset)
val bestFeatures = fcbf.transform(dataset)

Release

The latest version is : 0.1.0 / Date: 2018-09-28  / Scala version: 2.11.12

Reference

H.-L. Nguyen, Y.-K. Woon, W.-K. Ng, L. Wan, Heterogeneous ensemble for feature drifts in data streams, in: Proceedings of the 16th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining - Volume Part II, PAKDD’12, 2012, pp. 1–12.