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Replace these with `from_raw_data`:
1. `plot.confusion_matrix(y_test, y_pred)`
2. `plot.roc(y_test, y_pred)`
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**Is your feature request related to a problem? Please describe.**
There's no algorithm for Random Forest implementation for Machine Learning using python.
**Describe the solution you'd like**
Im…
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This project involves predicting the duration of NYC taxi trips using various regression models. The notebook includes steps for data exploration, preprocessing, model training, and evaluation.
## …
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To improve the MLacc performance, a neural network could be implemented to accept all input variables and predict multiple response variables at the same time. This requires modifying `ML.py` and `tra…
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Thanks for sharing the code and dataset,
I couldn't find the random forest code in the repo, and I tried to train it myself but I couldn't get the accuracy reported in the paper:
> RF/Frequential…
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Welcome to 'DSWP' Team, good to see you here.
This issue will helps readers in acquiring all the knowledge to learn about getting involved with Random Forest Algorithm. Tutorial to Random Forest Al…
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as touched in the dev telco today: it could also be an option to leave mtry/max_variables out of the spec for now (backends will be able to pick a good enough default behavior), and just introduce it…
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`REEMForest()` consistently produces an error with with several different datasets. Seems to be coming from `solve()` in `moy()` functions. This appears to be common problem. See [https://stackoverflo…
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Create an option in RF to get confidence bands. Base the results on building some sort of kernel density estimate from each tree.
Classification and regression.
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Currently the monotone constraints is available for xgboost and gbm. It would be great if this feature can be added to DRF to ensure local monotonicity. Currently there is no R package can achieve thi…