[MLLIB] SPARK-2303: Poisson regression model for count data #1243
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Refer to this link for build results: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/16201/ |
…cludes 1)the gradient of the negative log-likelihood, 2)the implementation of PoissonRegressionModel, the generalized linear algorithm class which uses L-BFGS and SGD for parameter estimation respectively, 3) the test suites for the gradient/loss computation, the regression method on generated and real-world data set, and 4) a Poisson regression data generator in mllib/util for producing the test data.
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Fixed scalastyle. |
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The implementations are merged into PR #1237, which is a combined effort for Poisson and Gamma regression. So I will close this. |
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This pull request includes the implementations of Poisson regression in mllib.regression for modeling count data. In detail, it includes:
JIRA: https://issues.apache.org/jira/browse/SPARK-2303