Not all pythons belong to one homogeneous group. Modern classification of snakes places the family Pythonidae under numerous genera determined by phylogenetic lineage, physical features, genetic data ...

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...

Machine learning algorithms are widely used for disease prediction, but the choice of sampling method is a factor that affects model performance, particularly in large populations, limitations on the ...

This set of notebooks enables the analysis of comorbidities associated with male infertility using structured EHR data. First, we identified nonoverlapping patients with male infertility and patients ...

This repository contains an analysis of the Kaggle Machine Learning & Data Science Survey dataset, focusing on salary prediction using ordinal logistic regression and other classification models.

In my 29th article, we delved into the fascinating world of Machine Learning (ML) and explored one of its foundational algorithms: Linear Regression. In this article, we’re taking the next step in our ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Dr. James McCaffrey of Microsoft Research presents a full demo of k-nearest neighbors classification on mixed numeric and categorical data. Compared to other classification techniques, k-NN is easy to ...

Regression in autism refers to the backtracking of skills, often in communication, social interaction, or daily functioning. Regression in autism is a condition where an individual with autism ...

Logistic regression is a popular and widely used statistical method for binary classification. It is a type of regression analysis used for predicting the outcome of a categorical dependent variable ...