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### Describe the bug
If I load my pre trained model and set of samples and call predict() multiple times I get different predicted classes. Here are some sample results. I am using a juypter noteb…
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Defining a treatment effect for the causal random survival forest requires specification of a horizon timepoint.
Should we use the same horizon for all datasets in our main analysis or use data-spe…
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We are continuing to develop our algorithms specifically with Random Forest algorithm this time.
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The paper mentions using traditional machine learning methods, such as LR (Logistic Regression) and RF (Random Forest). How did you extract the features for these methods?
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- Random forest
- sklearn docs
- https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html
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- [ ] why does test data performance deteriorate with more predictor variables?
- [ ] why do is the test data under predicting for RF compared with observed? Is it because the observed values haven't…
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c5.9xlarge (18 cores, HT off):
**1M:**
**Lightgbm:**
```
suppressMessages({
library(data.table)
library(ROCR)
library(lightgbm)
library(Matrix)
})
set.seed(123)
d_train
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Hello, I have a new model request: Mixed effect random forest (MERF). There are a few packages that support them in R. I'm not sure if this is the proper package for it.
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random forest简介
- random forest是目前非常流行的一种机器学习模型。
- random forest是弱决策模型。 所谓弱决策, 就是集中很多意见,不论意见的可信度到底如何。正所谓三个臭皮匠顶一个诸葛亮,在很多情况下你会发现它的表现可能比一个专家的意见更有效。
- 为什么random forest有如此奇效呢?
根据the law of large …
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