Learn how to build a multivariate linear regression model step by step—no libraries, just pure C++ logic!

Article citations More>> Kirasich, K., Smith, T. and Sadler, B. (2018) Random Forest vs Logistic Regression: Binary Classification for Heterogeneous Datasets. SMU Data Science Review, 1, Article 9.

This article will cover the basic theory behind logistic regression, the types of logistic regression, when to use them and take you through a worked example.

Want to understand logistic regression? Explore our guide to learn its applications and advantages in data analysis.

Covariations in univariate logistic regression analysis were tested for multicollinearity and then a multivariate logistic regression analysis was performed. If either the tolerance (Tol) was less ...

Univariate analysis can be used to assess the association between the investigated factor and the treatment result. However, multivariate analysis (multivariate logistic regression) provides a ...

Heart disease has turned into the most critical human disease and Heart failure rate has been increased. Accurate diagnosis and timely treatment is needed to prevent deaths. In this work, the heart ...

Multivariate analysis helps to understand the relationships between dependent variables; this methodology has great potential in several areas of knowledge. The aim of this study was to adjust and ...

Logistic regression is a machine learning technique for binary classification. For example, you might want to predict the sex of a person (male or female) based on their age, state where they live, ...