[jira] [Created] (SPARK-8298) Sliding Window CrossValidator

["Justin Yip (JIRA)" <ji...@apache.org>]

Justin Yip created SPARK-8298:
---------------------------------

             Summary: Sliding Window CrossValidator
                 Key: SPARK-8298
                 URL: https://issues.apache.org/jira/browse/SPARK-8298
             Project: Spark
          Issue Type: Improvement
          Components: ML
            Reporter: Justin Yip


CrossValidator only supports k-folds. It cannot prevent the validation data from look-ahead bias. I would like to contribute a sliding-window based CrossValidator. The sliding window guarantees a clear cutoff time between the training and validation data, to prevent look-ahead bias.

Three parameters are used to govern the generation process.
1. numFold - Int
2. firstCutoffTime - Timestamp, the cutoff time of the training data for the first (training, validation) data pair
3. validationWindowSize - Long, millis of the validation data set duration.

Need to decide:
Whether to make the current CrossValidator more generic or implement a new SlidingWindowCrossValidator.
- Most of the logic are identical between CrossValidator and SlidingWindowValidator, except for the part where the training-validation data pairs is generated. More, if we introduce other kinds of data splitting methods, there will be lots of code redundancy if we use multiple classes.
- However, I also foresee that things will get messy to support too many splitting methods with one CrossValidator class.





--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org