[SPARK-1457] Change APIs for training algorithms to take optimizer as parameter

• Type: Improvement
• Status: Resolved
• Priority: Minor
• Resolution: Won't Fix
• Component/s: MLlib
• Assignee: Unassigned
• Reporter: DB Tsai
• Created: 09/Apr/14 21:20
• Updated: 07/Nov/16 18:03
• Resolved: 24/Apr/15 22:24

Description

Currently, the training api has signature like LogisticRegressionWithSGD.

If we want to use another optimizer, we've two options, either adding new api like LogisticRegressionWithNewOptimizer which causes 99% of the code duplication, or we can re-factorize the api to take the optimizer as an option like the following.

class LogisticRegression private (
var optimizer: Optimizer)
extends GeneralizedLinearAlgorithm[LogisticRegressionModel]

Issue Links

• relates to: SPARK-1856 Standardize MLlib interfaces
• relates to: SPARK-5256 Improving MLlib optimization APIs
• relates to: SPARK-18303 CLONE - Improving MLlib optimization APIs