Comments (3)
Which learner are you using? How large is your dataset? How much memory did you allocate?
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I tried using RegressionTreeLearner with both LSBoostLearner and LADBoostLearner, both have the same problem.
I have up to about 124,000 training examples (with about 400 dimensions) and 10,000 test examples.
The amount of memory taken by a single thread is of the order of 4-8GB or so, but the amount fluctuates up and down by about 1-2GB every several seconds (the downward fluctuations are due to garbage collection).
Viewing CPU usage activity while running several regressors in different threads shows all the cores floating between about 20 and 60%, with major churn. This is indicative of heavy GC activity. Multithreaded Java programs that allocate no new objects keep all the cores busy at 100%.
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I just made some edits to save memory. Let me know if that helps. Thank you!
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Related Issues (14)
- Need for programmatic setup of datasets HOT 2
- Documentation is missing many important details HOT 4
- could you provide some working data set?
- Add MLTK to Maven Central HOT 1
- Support for data already in program HOT 2
- JAR file HOT 1
- "mvn clean package" doesn't work HOT 7
- How to run GA2M with FAST? HOT 2
- is normalization step needed in feature preparation? HOT 1
- ElasticNet results inconsistent HOT 1
- Residuals not saved when building GAM HOT 4
- Typo in DoublePairComparator HOT 1
- GAM plots with nominal interaction terms HOT 2
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