Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Interestingly, the study also identified a counterintuitive negative association between heavy alcohol consumption and depression, as well as between higher BMI and depression risk, challenging ...

This project trains and evaluates a logistic regression model using Apache Spark to predict whether a person earns more than $50K/year based on demographic data from the UCI Adult dataset.

The model is created using Logistic Regression, which is a supervised classification algorithm.

The following variables were taken into account: age at disease onset, follow-up length, gender, ACR/EULAR classification criteria for ... laboratory variables with the package FactoMineR. Logistic ...

To address these challenges, this article constructs a novel integrative model called tensor decomposition-based relaxed linear regression (TDRLR) for HSI classification. First, the model adopts ...