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- Running the examples notebooks
- Running with custom data
- XGBoost (rust implementation) has negative R2 score value for regression and classification tasks
- I tried changing the hyper-paramete…
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**Installation**
https://medium.com/@vivek.yadav/deep-learning-setup-for-ubuntu-16-04-tensorflow-1-2-keras-opencv3-python3-cuda8-and-cudnn5-1-324438dd46f0
**Introduction to Statistics for Data S…
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### Description
`xgboost_ray.train` can accept a list of parquet or csv files in a RayDMatrix object as input ([ref](https://github.com/ray-project/xgboost_ray#distributed-data-loading)). This does n…
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### ML-Crate Repository (Proposing new issue)
:red_circle: **Profinity filter** :
:red_circle: ** Aim is to classify whether the used text is abusive or not ** :
:red_circle: **Dataset** :
:red_ci…
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Hello Everyone
Not sure if I'm doing something wrong or this is the default behavior. I have a server with following specs
32 x Intel(R) Xeon(R) CPU E5-2640 v2 @ 2.00GHz (2 Sockets)
Memory 125…
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I have a highly skewed dataset. I was hoping that Tpot will make use of parameters like `class_weight` (in logistic regression) and `scale_pos_weight` (Xgboost) but it doesn't recognize the class dist…
Ak784 updated
3 years ago
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Currently `lm`, `glm`, `MASS::glm.nb`, `brms::brm`
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## Short Description
Hi, I have been wordering if there is a way to connect the bart regression model with some other tree based model, like XGboost or sklearn's trees. This in order to use the bar…
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Environment
AWS EMR Serverless 7.0.0
PySpark 3.5.0
XGBoost 2.0.3
I’m using XBoost for regression, specifically the SparkXGBRegressor. I’m able to use it without issues on my local machine. How…
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This is currently broken in the latest GitHub versions, which are required since CRAN versions of mlr3 and mlr3mbo are not compatible if I remember correctly, as I'm getting:
```
Learner (surv.xgb…