The main goal of this paper is to present and evaluate the possibility of using the methods and tools of Artificial Intelligence and Data Mining to analyze marketing data needed to support decision-making in the process of market segmentation. This paper describes the application of Kohonen’s Neural Networks and Classification Trees (including tools such as CART-Classification and Regression Tr...

This study proposes an unsupervised learning approach for the task of hand pose recognition. Considering the large variation in hand poses, classification using a decision tree seems highly suitable for this purpose. Various research works have used boosted decision trees and have shown encouraging results for pose recognition. This work also employs a boosted classifier tree learned in an unsu...

This study envisages assessing the effects of COVID-19 on on-time performance US-airlines industry in disrupted situations. The deep learning techniques used are neural network regression, decision forest boosted tree regression and multi class logistic regression. best technique is identified. In perspective data analytics, it suggested what airlines should do for situation. performances all m...

In this paper we apply a Monte-Carlo Tree Search implementation that is boosted with domain knowledge to the game of poker. More specifically, we integrate an opponent model in the Monte-Carlo Tree Search algorithm to produce a strong poker playing program. Opponent models allow the search algorithm to focus on relevant parts of the game-tree. We use an opponent modelling approach that starts f...

Nowadays decision tree learning is one of the most popular classification and regression techniques. Though decision trees are not accurate on their own, they make very good base learners for advanced tree-based methods such as random forests and gradient boosted trees. However, applying ensembles of trees deteriorates interpretability of the final model. Another problem is that decision tree l...