3 papers
cs.LG2026
Variable Splitting Binary Tree Models Based on Bayesian Context Tree Models for Time Series Segmentation
Yuta Nakahara, Shota Saito, Kohei Horinouchi +4
We propose a variable splitting binary tree (VSBT) model based on Bayesian context tree (BCT) models for time series segmentation. Unlike previous applications of BCT models, the t…
cs.LG2024
An Algorithmic Framework for Constructing Multiple Decision Trees by Evaluating Their Combination Performance Throughout the Construction Process
Keito Tajima, Naoki Ichijo, Yuta Nakahara +1
Predictions using a combination of decision trees are known to be effective in machine learning. Typical ideas for constructing a combination of decision trees for prediction are b…
cs.IT2021
An Efficient Bayes Coding Algorithm for the Non-Stationary Source in Which Context Tree Model Varies from Interval to Interval
Koshi Shimada, Shota Saito, Toshiyasu Matsushima
The context tree source is a source model in which the occurrence probability of symbols is determined from a finite past sequence, and is a broader class of sources that includes…