Xusen Yin created SPARK-12098: --------------------------------- 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org