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Hello I'm new to using the cuml and dask.
I am trying to use random forest using cuml with dask for multiple GPUs. But the prediction part won't finish.
It keeps on saying that its restarting the …
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Is there a way to see what is under the hood of the random forest? Is there a way to get the parameters of a trained model? Or maybe you can get the individual decisions trees as a nested-if-statement…
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你好,
我是一个计算机视觉在读博士生,读到你以前的文章受到很多启发,不知道相关的源代码是否是公开的?
“Multiview Random Forest of Local Experts Combining RGB and LIDAR data for Pedestrian Detection"
谢谢。
Yifei
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The random forest has no good validation strategies. Therefore it was necessary to visualize the data with a different approach.
### Accomplishes
- [x] Import Library Seaborn
- [x] Univariate distri…
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Hi, everyone. Thank you for posting this fancy package.
I want to test whether a heterogeneous treatment effect exists in my instrumental forest model.
For your information, the sample size is aroun…
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`{xgboost}` can fit boosted, penalized linear models by setting `booster="gblinear"`. This would be a great addition to `linear_reg()`, or perhaps there can be a `boost_linear_reg()` function and it c…
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@rudecat raised some good domain knowledge considerations like the fact that the number of successful scores should never be greater than the number of attempted scores. We should think of more checks…
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Hello,
I'm very interested in fitting random forests for binary classification using collections of explanatory variables of various types that also vary in the numbers of unique values they contai…
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In the case of Binary treatment[1 for treatment group 0 for control group] and Continuous outcome,
CASE1 : discrete_treatment=True
# est = CausalForestDML(criterion='het')
# set parameters for c…
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I think it might be worth creating a category for packages that deal with sparse data well --- this is extremely important for all sorts of NLP and recommendation applications, where very large and ve…