[SPARK-4736] functions returning the category with weights

• Type: Improvement
• Status: Resolved
• Priority: Major
• Resolution: Duplicate
• Component/s: MLlib
• Assignee: Unassigned
• Reporter: yu jiang
• Created: 04/Dec/14 04:40
• Updated: 27/Apr/15 18:59
• Resolved: 27/Apr/15 18:59

Description

In this version, we add two functions: 1) predictByVotingWithWeight(features: Vector) and 2) predictWithWeight(features: Vector). And we also modify the function: predictByVoting(features: Vector). There are at least two reasons why we make such improvement: 1) In our practice, we want to find the top N samples from one category. However in 1.3.0 version, the function of predict can only give the predicted category but without weights. 2) What's more, in our practice, the numbers of positive and negative samples are very unbalance. There are much less positive samples than negative samples. According to the results of votes, there are very few samples predicted as positive sample. If the weights are also given, users can make a proper threshold to modify the results so that the performance can be improved.

Issue Links

• duplicates: SPARK-3727 Trees and ensembles: More prediction functionality
• links to: [Github] Pull Request #3583 (dikejiang)