Abstract: In this paper, we have studied three well-known classification algorithms: (1) Decision Tree, (2) Naïve Bayesian Classifier, and (3) Naïve Bayesian Tree for supervised learning in machine ...

Abstract: In practical classification problems, imbalanced class distribution is very common. Traditional classification methods usually aim at optimizing the overall accuracy, which leads to ...

The Esports Advocate has learned that Berlin-based esports data firm Bayes Esports Solutions GmbH was put under administration and filed for insolvency in late May (case no. 3602 IN 3585/25). On Aug.

Bayesian classification techniques form a cornerstone of data mining, combining probabilistic modelling with statistical inference to deliver transparent and computationally efficient classifiers. At ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the naive Bayes regression technique, where the goal is to predict a single numeric value. Compared to other ...

The goal of a machine learning regression problem is to predict a single numeric value. There are roughly a dozen different regression techniques such as basic linear regression, k-nearest neighbors ...

ABSTRACT: Background: Unsafe abortion (USA) is defined as the termination of a non-desired pregnancy, performed by an unqualified person or in an environment without minimum medical standards, or both ...

Multi-label text classification (MLTC) assigns multiple relevant labels to a text. While deep learning models have achieved state-of-the-art results in this area, they require large amounts of labeled ...

I have used Multinomial Naive Bayes, Random Trees Embedding, Random Forest Regressor, Random Forest Classifier, Multinomial Logistic Regression, Linear Support Vector Classifier, Linear Regression, ...

Project involved the building and training of machine learning models using the custom built kNN and bayesian classifier as well as the classifiers from the python sklearn library.