forest-confidence-interval
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Confidence intervals for scikit-learn forest algorithms
Hi, I am trying to generate confidence intervals for the below sample data. I am using RandomForestRegressor with bootstrapping enabled. X_train shape (270, 7) [[ 12. 20. 1. ... 300....
When using `random_forest_error()` with a dataset in which the features range between 0 and 1 and of datatype `float64`, I get a bunch of overflow errors like so: ``` /Users/erictaw/forest-confidence-interval/forestci/calibration.py:86:...
Hi, I'm trying to create error estimates and am using RandomForestRegressor with bootstrapping enabled. I am using data with dimensions: x_test [10,13] x_train [90,13] y_test [10,2] y_train [90,2] I then...
On a toy problem, in which I am using Random Forests + ForestCI to prototype some ideas, I will randomly get NaNs in the `V_IJ` estimates. This toy problem is...
For my dataset, I tried correlating the CIs to absolute error on the test set, and didn't find a relationship. I do get a relationship if I use the standard...
I’m looking at using random forest regressors to perform hyperparameter tuning in a Bayesian optimization setup. While you can use the upper confidence bound to explore your state space, Thompson...
Hi there, I believe the centered predictions are being computed incorrectly. Line 278 in `forestci.py` takes the average over the _predictions_, as opposed to the trees. The resulting shape of...
Training set is of the form (n_training_samples, n_features) = (14175.34) Testing set is of the form (n_testing_samples, n_features) = (4725,34) Running - forestci.random_forest_error(randomFor, X_train, X_test) Yields the following error; ValueError...
Hi folks, I'm trying to use fci but when I run: import forestci as fci I get: /opt/conda/lib/python3.6/site-packages/forestci/forestci.py in 9 import copy 10 from .calibration import calibrateEB ---> 11 from...
I have encountered this warning message when executing `forestci.random_forest_error(regressor, x_train, x_test)` ``` RuntimeWarning: invalid value encountered in true_divide g_eta_main = g_eta_raw / sum(g_eta_raw) ``` and the results are ``` array([nan,...