PredictionInterval

Obtain prediction intervals for input models

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PredictionInterval

teller.PredictionInterval(obj, method="splitconformal", level=0.95, seed=123)

Class PredictionInterval: Obtain prediction intervals.

Attributes:

obj: an object;
    fitted object containing methods `fit` and `predict`

method: a string;
    method for constructing the prediction intervals. 
    Currently "splitconformal" (default) and "localconformal"

level: a float;                
    Confidence level for prediction intervals. Default is 0.95, 
    equivalent to a miscoverage error of 0.05

seed: an integer;
    Reproducibility of fit (there's a random split between fitting and calibration data)

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fit

PredictionInterval.fit(X, y)

Fit the method to training data (X, y).

Args:

X: array-like, shape = [n_samples, n_features]; 
    Training set vectors, where n_samples is the number 
    of samples and n_features is the number of features.

y: array-like, shape = [n_samples, ]; Target values.

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predict

PredictionInterval.predict(X, return_pi=False)

Obtain predictions and prediction intervals

Args:

X: array-like, shape = [n_samples, n_features]; 
    Testing set vectors, where n_samples is the number 
    of samples and n_features is the number of features.

return_pi: boolean               
    Whether the prediction interval is returned or not. 
    Default is False, for compatibility with other _estimators_.
    If True, a tuple containing the predictions + lower and upper 
    bounds is returned.

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