Xusen Yin created SPARK-12098:
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Summary: Cross validator with multi-arm bandit search
Key: SPARK-12098
URL: https://issues.apache.org/jira/browse/SPARK-12098
Project: Spark
Issue Type: New Feature
Components: ML, MLlib
Reporter: Xusen Yin
The classic cross-validation requires all inner classifiers iterate to a fixed
number of iterations, or until convergence states. It is costly especially in
the massive data scenario. According to the paper Non-stochastic Best Arm
Identification and Hyperparameter Optimization
(http://arxiv.org/pdf/1502.07943v1.pdf), we can see a promising way to reduce
the amount of total iterations of cross-validation with multi-armed bandit
search.
The multi-armed bandit search for cross-validation (bandit search for short)
requires warm-start of ml algorithms, and fine-grained control of the inner
behavior of the corss validator.
Since there are bunch of algorithms of bandit search to find the best parameter
set, we intent to provide only a few of them in the beginning to reduce the
test/perf-test work and make it more stable.
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