Package

org.apache.spark.mllib

odkl

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package odkl

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  1. class IsotonicRegression extends Serializable with Logging

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    Isotonic regression.

    Isotonic regression. Currently implemented using parallelized pool adjacent violators algorithm. Only univariate (single feature) algorithm supported.

    Sequential PAV implementation based on: Tibshirani, Ryan J., Holger Hoefling, and Robert Tibshirani. "Nearly-isotonic regression." Technometrics 53.1 (2011): 54-61. Available from http://www.stat.cmu.edu/~ryantibs/papers/neariso.pdf

    Sequential PAV parallelization based on: Kearsley, Anthony J., Richard A. Tapia, and Michael W. Trosset. "An approach to parallelizing isotonic regression." Applied Mathematics and Parallel Computing. Physica-Verlag HD, 1996. 141-147. Available from http://softlib.rice.edu/pub/CRPC-TRs/reports/CRPC-TR96640.pdf

    Annotations
    @Since( "1.3.0" )
    See also

    Isotonic regression (Wikipedia) ODKL Patches:

    1. view before slice for better performance 2. Per partition sorting instead of global order for smother data distribution

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