Decision trees are some of the most popular and intuitive classification techniques. Based on the recursive division of the data, the goal is to ultimately identify regions in the space in which most instances belong to the same class. This paper proposes a game-theoretic decision tree using a two-player game to determine the splitting…
Decision trees and random forests are some of the most popular machine learning tools for binary classification, being used in many practical applications. Both methods provide a neighborhood for tested data during the prediction phase, and probabilities are usually computed based on the proportion of classes in those neighborhoods. The approach presented in this…
Cooperative-competitive social group dynamics may be modelled with multi-agent environments with a large number of agents from a few distinct agent-types. Even the simplest games modelling social interactions are suitable to analyze emerging group dynamics. In many cases, the underlying computational problem is NP-complex, thus various machine learning techniques are implemented to accelerate the…
Breast cancer is the most commonly diagnosed type of cancer. It is essential to classify patients as quickly as possible into groups with a high or low risk of cancer, to provide adequate treatment. This paper aims to address the impact of the parameters of convolutional neural networks in the binary classification of mammograms.…
Breast cancer causes numerous deaths worldwide; yet the numbers have decreased in the past years as a result of computer-aided diagnosis and proper treatment. The current paper is addressed to the base of such diagnosis system: pre-processing and segmentation. After a robust pre-processing, an unsupervised version of GrowCut is applied to define the location…
A game theoretic flavoured decision tree is designed for multi-class classification. Node data is split by using a game between sub-nodes that try to minimize their entropy. The splitting parameter is approximated by a naive approach that explores the deviations of players that can improve payoffs by unilateral deviations in order to imitate the…
Twitter Sentiment Analysis is demanding due to the freestyle way people express their opinions and feelings. Using only the preprocessed text from a dataset does not bring enough value to the process. Therefore, there is a need to define and mine different and complex features to detect hidden information from a tweet. The proposed…
The purpose of this work is to study the possible approaches to build a recommendation system that could help students in organizing their work and improving their results. More specifically, we intend to predict grades of a student for future exams, based on his/her previous results and the past grades received by all students…
Nowadays, software systems evolve in vast and complex applications. In such a complex system, a minor change in one part may have unexpected degradation of the software system design, leading to an unending chain of bugs and defects. Therefore, to keep track of implications that could appear after a change has been applied, the…
Introduction: Multiparametric magnetic resonance imaging (mpMRI) is the main imagistic tool employed to assess patients suspected of harboring prostate cancer (PCa), setting the indication for targeted prostate biopsy. However, both mpMRI and targeted prostate biopsy are operator dependent. The past decade has been marked by the emerging domain of radiomics and artificial intelligence (AI),…