ade_hat-class

Predictions produced by a <code><a rd-options="" href="/link/ADE-class?package=tsensembler&version=0.1.0" data-mini-rdoc="tsensembler::ADE-class">ADE-class</a></code> object.
It contains y_hat, the combined predictions,
Y_hat, the predictions of each base model,
Y_committee, the base models used for prediction
at each time point, and E_hat, the loss predictions
by each meta-model.

internal

A framework for dynamically combining forecasting models for time series forecasting predictive tasks. It leverages machine learning models from other packages to automatically combine expert advice using metalearning and other state-of-the-art forecasting combination approaches. The predictive methods receive a data matrix as input, representing an embedded time series, and return a predictive ensemble model. The ensemble use generic functions 'predict()' and 'forecast()' to forecast future values of the time series. Moreover, an ensemble can be updated using methods, such as 'update_weights()' or 'update_base_models()'. A complete description of the methods can be found in: Cerqueira, V., Torgo, L., Pinto, F., and Soares, C. "Arbitrated Ensemble for Time Series Forecasting." to appear at: Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2017; and Cerqueira, V., Torgo, L., and Soares, C.: "Arbitrated Ensemble for Solar Radiation Forecasting." International Work-Conference on Artificial Neural Networks. Springer, 2017 <doi:10.1007/978-3-319-59153-7_62>.

Vitor Cerqueira

tsensembler

Dynamic Ensembles for Time Series Forecasting

Luis Torgo

Carlos Soares

ade_hat-class function

<dl class="dl-horizontal">
<dt><code>y_hat</code></dt><dd>combined predictions of the ensemble
<code><a rd-options="" href="/link/ADE-class?package=tsensembler&version=0.1.0" data-mini-rdoc="tsensembler::ADE-class">ADE-class</a></code>. A numeric vector;</dd></dl><dt><code>Y_hat</code></dt><dd>a matrix containing the predictions made by
individual models;</dd><dt><code>Y_committee</code></dt><dd>a list describing the models selected for
predictions at each time point (according to lambda
and omega);</dd><dt><code>E_hat</code></dt><dd>predictions of error of each base model, estimated
by their respective meta model associate;</dd>

Slots

Predictions produced by a <code><a rd-options='' href='ADE-class'>ADE-class</a></code> object.
It contains y_hat, the combined predictions,
Y_hat, the predictions of each base model,
Y_committee, the base models used for prediction
at each time point, and E_hat, the loss predictions
by each meta-model.

ade_hat-class: Predictions by an ADE ensemble

Description

Arguments

Slots

See Also