We present a framework called TLF that builds a classifier for the target domain having only few labeled training records by transferring knowledge from the source domain having many labeled records. While existing methods often focus on one issue and leave the other one for the further work, TLF is capable of handling both issues simultaneously…
data-science data-mining random-forest transfer-learning decision-trees concept-drift maching-learning domain-adaptation manifold-optimization random-forest-classifier decision-forest heterogeneous-domain-adaptation feature-discrepensy distribution-divergence
-
Updated
Mar 25, 2023 - Java