predict.conformalRegressor

Conformal time series forecasting using the caret infrastructure.
It provides access to state-of-the-art machine learning models for forecasting
applications. The hyperparameter of each model is selected based on time
series cross-validation, and forecasting is done recursively.

Resul Akay

caretForecast

Conformal Time Series Forecasting Using State of Art Machine
Learning Algorithms

predict.conformalRegressor function

<dl><dt>object</dt>
<dd>A conformalRegressor object</dd>
<dt>y_hat</dt>
<dd>Predicted values</dd>
<dt>sigmas</dt>
<dd>Difficulty estimates</dd>
<dt>confidence</dt>
<dd>Confidence level</dd>
<dt>y_min</dt>
<dd>The minimum value to include in prediction intervals</dd>
<dt>y_max</dt>
<dd>The maximum value to include in prediction intervals</dd>
<dt>...</dt>
<dd>Ignored</dd></dl>

Arguments

Author

Predict a conformalRegressor — predict.conformalRegressor

<dl>

<dt>object</dt>
<dd>A conformalRegressor object</dd>


<dt>y_hat</dt>
<dd>Predicted values</dd>


<dt>sigmas</dt>
<dd>Difficulty estimates</dd>


<dt>confidence</dt>
<dd>Confidence level</dd>


<dt>y_min</dt>
<dd>The minimum value to include in prediction intervals</dd>


<dt>y_max</dt>
<dd>The maximum value to include in prediction intervals</dd>


<dt>...</dt>
<dd>Ignored</dd>

</dl>

predict.conformalRegressor: Predict a conformalRegressor

Description

Usage

Value

Arguments

Author