Characterization and classification of dynamical states of a system using persistent homology (PH) is proving to be rather fruitful in recent years. The marked success of the approach lies in mapping ...
1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...
The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...
Where understanding is refined, and insights are illuminated. (1) Goran Muric, InferLink Corporation, Los Angeles, (California gmuric@inferlink.com); (2) Ben Delay, InferLink Corporation, Los Angeles, ...
ABSTRACT: This paper presents a comprehensive machine learning approach for credit score classification, addressing key challenges in financial risk assessment. We propose an optimized CatBoost-based ...
Cluster analysis can be used on symptom and behavior data to identify groups of similar individuals who may share underlying disease etiology or health risks. However, there are few clustering methods ...
A good way to see where this article is headed is to take a look at the screenshot in Figure 1. The demo program begins by loading a 200-item set of training data and a 32-item set of test data into ...
Abstract: Multiclass classification problems are often addressed by decomposing them into a set of binary classification tasks. A critical step in this approach is the effective aggregation of ...
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