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Export the transfer boosted model to a lgbm/xgboost to speed up execution.
A potential solution is to use dump_model with virtual file processing.
https://stackoverflow.com/questions/18550127/ho…
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Hi team, I'm using hummingbird_ml==0.4.3 and xgboost==1.5.2, and testing on XGBRegressor with objective reg:tweedie predictions.
```
import xgboost as xgb
import pandas as pd
import hummingbird
…
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Let is assume I have a dataset with 3 independent valiables/predictors/features. So far I used code along those lines successfully:
```
hyperparameters = {
'max_depth': '10',
'nu…
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**Is your feature request related to a problem? Please describe.**
Currently when librmm is built, it accepts a CMake option `CUDA_STATIC_RUNTIME` to determine whether to link to cudart statically or…
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Xgboost supports categorical values directly, without going through a one-hot sparse array.
In the example below, I specify the `a` series to be a categorical int type. Then I pass the `enable_catego…
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/kind feature
**Describe the solution you'd like**
[A clear and concise description of what you want to happen.]
Add a sample of MMS using XGBoost model server similar to [sklearn](https://github…
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when I load xgboost model return errs,model is trained for xgboost4j。
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It currently prints out
```
07-28 14:02:38.516 127.0.0.1:54321 18034 main INFO: Cannot initialize XGBoost backend! Xgboost (enabled GPUs) needs:
07-28 14:02:38.516 127.0.0.1:54321 18034 main INFO…
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I get the following error when trying to generate the large-v3 quantized coreml model:
```
$ ./models/generate-coreml-model.sh large-v3-q5_0
scikit-learn version 1.3.0 is not supported. Minimum req…
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Hi I'm trying to convert an XGBClassifier to onnx and noticed that if I use a large number of n_estimators and then use early_stopping argument, convert the model to onnx and then load and run the mod…