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Hi there,
I'm looking to use xgboost as my nuisance model in my DoubleML setup and use xgboost's own mechanism for encoding categorical features (rather than having to one hot encode them myself).
…
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panic: runtime error: makeslice: len out of range
goroutine 1 [running]:
github.com/dmitryikh/leaves/internal/xgbin.ReadString(0x140000940c0)
go/pkg/mod/github.com/dmitryikh/leaves@v0.0.0-202…
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Hello,
I'm developing a library for decision tree visualization https://github.com/mljar/supertree and would appreciate feedback on whether my visualization approach for XGBoost is correct. I've comp…
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The CLI usage is confusing at best and it needs to be reworked to be easy to understand and consistent.
- [ ] drop the concept of --optical and --disk and rename both to --device. anvil already kno…
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Until now, XGB seems the most credible tabular model algorithm.
Also, histogram-based XGboost is a CPU-trainable model algorithm.
And also, when we validate the model in other CDM databases, XGboo…
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如下图所示：XGB训练右键配置的时候，需要选择ID列名称，标签（Y）列名称
但实际上，在XGB的训练的源码中https://github.com/secretflow/teeapps/blob/main/teeapps/biz/xgb/xgb.py#L58
并没有引用到前端配置中的ID列名称、标签列名称，而是直接使用 task_config.inputs[0].schema.lables …
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Implement training with default parameters same as in [this kaggle kernel](https://www.kaggle.com/iprapas/ideas-from-kernels-and-discussion-lb-1-135) aiming to achieve similar feature importances. Do …
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Once DNN training is complete, we should begin our inference on the same fields as analyzed by the XGB algorithm to compare the results from each. The comparison may identify areas of improvement for …
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Hi there,
My end goal is to summarize SHAP values across CV splits, I tried the method outlined [here](https://colab.research.google.com/gist/L-Ramos/743319d0c405b386d481c924e0fc6789/shap_cross_val…
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I encountered the following error while simulating with Vivado, it seems that some files are missing.
Vivado Simulator v2022.1
Copyright 1986-1999, 2001-2022 Xilinx, Inc. All Rights Reserved.
Run…