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This is prediction model is based on Random Forest Regressor.
Use a better model like SVM Regressor to give better predictions.
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**Is your feature request related to a problem? Please describe.**
When a user wants to train a very large dataset, there is a constraint in the largest model he can train because the same GPU contai…
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```Traceback (most recent call last):
File "", line 1, in
File "/virtualenvs/smartshift-load-forecasting-9TtSrW0h-py3.9/lib/python3.9/site-packages/sklearn_json/__init__.py", line 122, in to_js…
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Right now neither [random_forest_classifier](https://github.com/smartcorelib/smartcore/blob/development/src/ensemble/random_forest_classifier.rs) nor [random_forest_regressor](https://github.com/smart…
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See in the following image that "Atributo(s) previsor(es)", "Atributo usado como rótulo (label)", "Nome do atributo usado como predição" are not in the "right"/"common" place in the random forest regr…
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This is just to standardize with the classification models.
Currently, the output of a random forest regressor is just the metric RMSE:
.
All of turicreate's regress…
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**Describe the bug**
When running the random forest regressor on the same data set, we receive differing R2 values (this exists across versions 22.02, 22.04,22.06):
- Single GPU: positive R2 value…
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I'm trying to perform a regression analysis on an annual revenue using 130 variables (127 numeric variables and 3 categorical variables that have been label encoded). These are the parameters that I f…
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How does the predictive performance of the first stage models affect confidence in the final stage model?
For context, I am using the ForestDMLCateEstimator with a random forest regressor and rando…