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Here is a paper that uses Machine Learning to build High-Resolution Poverty Maps
https://www.sciencedirect.com/science/article/pii/S0305750X22002182
and is a great demonstration of how machine l…
mmcky updated
2 years ago
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it seems to me sklearn not supporting those code using native/standard xgboost api.
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I am working on a tricky classification problem that has unbalanced classes (10 to 1 ratio), with around 200,000 instances and approximately 10 features.
I managed to get reasonable performance using…
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### Overview
When using caret to train an XGBoost model with parallelization at the resample level, execution continues indefinitely (or at least, for more than several hours in my tests), when the…
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Error: water.exceptions.H2OIllegalArgumentException: Fold column must be either categorical or contiguous integers from 0..N-1 or 1..N
at hex.ModelBuilder.cv_AssignFold(ModelBuilder.java:358)
at he…
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The 'lossguide' grow_policy used with h2o.xgboost does not appear to work under a gpu backend. I have tried updating the drivers and completely reinstalling the CUDA toolkit and while the algorithm wi…
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As reported on h2ostream: https://groups.google.com/forum/#!topic/h2ostream/F-E7Lzil284
There seems to be an issue on R for xgboost implementation:
Documentation for learn_rate and eta state th…
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I try to train a XGBoost model with a GPU instance (P3.16xlarge), but it reports error:
```
OSError: Job with key $03017f000001c68bffffffff$_908b7c8320882d5230bc213e87c44498 failed with an exception…
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Improvements suggested for XGBoost default models inside AutoML:
* xgBoostParameters._max_depth should not be 20 (XGB def2). The deepest we should go on this is probably 15 or 13. For reference d…
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Use H2O's automl library to try to improve on standard XGBoost approach.