A new approach called ABRF (the attention-based random forest) and its modifications for
applying the attention mechanism to the random forest (RF) for regression and classification …

This paper presents a causal discovery model for time series analysis, which can find
several causal lags of one variable over another, presenting the results by means of a …

A new attention-based model for the gradient boosting machine (GBM) called AGBoost (the
attention-based gradient boosting) is proposed for solving regression problems. The main …

New models of random forests jointly using the attention and self-attention mechanisms are
proposed for solving the regression problem. The models can be regarded as extensions of …

A new modification of the isolation forest called the attention-based isolation forest
(ABIForest) is proposed for solving the anomaly detection problem. It incorporates an …

This paper provides new models of the attention-based random forests called LARF (leaf
attention-based random forest). The first idea behind the models is to introduce a two-level …

A modification of the attention-based random forest (RF) called ABRF-PM is proposed. In
contrast to the original attention-based RF, the ABRF-PM model uses the imprecise pari …

An extension of the attention-based random forest called ABRF-E for incorporating the
attention mechanism into the random forest (RF) for improving the machine learning model …

An attention-based random survival forest (Att-RSF) is presented in the paper. The first main
idea behind this model is to adapt the Nadaraya-Watson kernel regression to the random …