image thumbnail

Maximum independence domain adaptation (MIDA)

version (32.2 KB) by Ke Yan
A feaure-level transfer learning (domain adaptation) algorithm


Updated 20 Apr 2016

View License

A domain-invariant subspace will be learned. MIDA can be applied in all kinds of domain adaptation problems, including discrete or continuous distributional change, supervised/semi-supervised/unsupervised, multiple domains, classification or regression, etc. All domains can be unlabeled/labeled/partially labeled. Suitable for transfer learning, domain adaptation, and concept drift adaptation (e.g. sensor drift correction) problems. Two test cases are in testMida.m.
ref: Ke Yan, Lu Kou, and David Zhang, "Domain Adaptation via Maximum Independence of Domain Features,"
Copyright 2016 YAN Ke, Tsinghua Univ. ,

Cite As

Ke Yan (2021). Maximum independence domain adaptation (MIDA) (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2011a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!