[MAHOUT-1621] k-fold cross-validation in MapReduce Random Forest example?

• Type: Question
• Status: Closed
• Priority: Major
• Resolution: Not A Problem
• Fix Version/s: 0.10.0
• Component/s: classic
• Labels: legacy

Environment

Ubuntu Linux 14.04

• Assignee: Unassigned
• Reporter: Tawfiq Hasanin
• Created: 14/Oct/14 14:35
• Updated: 31/Jan/24 22:17
• Resolved: 28/Mar/15 17:09

Description

My goal is to modify MapReduce Random Forest example by combining BuildForest.java and TestForest.java into a new class called RandomForest.java

The main point is to input one data file which is going to be used in training and testing; with k-fold cross-validation.

I have a big data with hight diminutional features and small amount of instances.

Seems to be a frustrating dead-end. is this process achievable? Or is it against MapReduce nature?

Thanks..