forest-confidence-interval

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First of all many thanks for the very nice repository and clean code! I was wondering whether this method would be applicable to non-binary classification tasks. By looking at the...

AlCorreia

All 0's in `g_eta_raw`.

3

Trying to debug the problem of getting all `NaN`'s from `random_forest_error` I found that the `g_eta_raw` array from https://github.com/scikit-learn-contrib/forest-confidence-interval/blob/bfb97c096287e74728132b8c7923590c2ad518e8/forestci/calibration.py#L101 contains all 0's and then the `g_eta_main` division throws the warning...

m0wer

When I use this on my Random forest model it only works when I use 200 or more trees in the parameters. n_trees = 200 forest = RandomForestRegressor(n_estimators=n_trees, random_state=42) my...

joachimder

V_IJ_unbiased is zero, when x_test = 1

3

Hi. I am trying to get a CI for a new x value that was not in the training set. ``` X_train.shape = 2000, 1 X_test.shape = 1, 1 X_test...

Maxfashko

Hi, I was using the random_forest_error() function for a project of mine where the data is of the order of 10,000 and if I used it without a scaler, it...

chahakmehta

Add low memory implementation of core computation

7

Computing confidence intervals on large datasets is extremely memory intensive because of the following matrix multiplication: inbag (n_train_samples, n_trees) X pred_centered.T (n_trees, n_test_samples) = result (n_train_samples, n_test_samples). I've added the...

owlas

progress indicator?

1

@owlas @arokem I'm running `fci.random_forest_error` on a fairly large dataset. ``` train: 3334431, 200 test: 13703350, 200 ``` (train is smaller after undersampling) I'm trying to use both the `memory_constrained`...

AlJohri

ValueError with random_forest_error() on multi-dimensional output

1

I'm getting a `ValueError` when using a random forest estimator trained on multi-dimensional output: ``` fci.random_forest_error(est, X_train, X_test) Traceback (most recent call last): File "", line 1, in fci.random_forest_error(est, X_train,...

mattrossman

confidence interval on train data

2

Hello, I am trying to compare the RF error on train and test data for a regression problem. After fitting the model (rf_model), I estimate the error as follows (np...

BSharmi

Halo. I started to use forest-confidence-interval. Thank you for implementing package. After several interaction I converged to following usage: ```` errors = fci.random_forest_error(clf, k0_training,k0_test,memory_constrained=1, memory_limit=100, calibrate=0 ) ```` ## I...

miranov25