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research-article

Testing exchangeability for transfer decision

Published: 01 March 2017 Publication History

Abstract

A novel solution to the problem whether to transfer based on exchangeablity test.Statistically testing if the source data is generated from the target distribution.The test is non-parametric and distribution free.Empirically justified the proposed test is effective for predicting transfer result. This paper introduces a non-parametric test to decide whether to transfer data from a source domain to a target domain to improve the generalization performance of predictive models on the target domain. The test is based on the conformal prediction framework: it statistically tests whether the target and source data are generated from the same distribution under the exchangeability assumption. The experiments show that the test is capable of outperforming existing methods when it decides on instance transfer.

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  1. Testing exchangeability for transfer decision

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    Published In

    cover image Pattern Recognition Letters
    Pattern Recognition Letters  Volume 88, Issue C
    March 2017
    88 pages

    Publisher

    Elsevier Science Inc.

    United States

    Publication History

    Published: 01 March 2017

    Author Tags

    1. 41A05
    2. 41A10
    3. 65D05
    4. 65D17
    5. Conformity prediction framework
    6. Exchangeability test
    7. Instance-transfer learning

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