The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

Businesspeople need to demand more from machine learning so they can connect data scientists’ work to relevant action. This requires basic machine learning literacy — what kinds of problems can ...

The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity. The goal of a ...

Last month we explored how to model a simple relationship between two variables, such as the dependence of weight on height 1. In the more realistic scenario of dependence on several variables, we can ...

The paper studies estimation of partially linear hazard regression models with varying coefficients for multivariate survival data. A profile pseudo-partial-likelihood estimation method is proposed.

Vector time series data are widely met in practice. In this paper we propose a multivariate functional-coefficient regression model with heteroscedasticity for modelling such data. A local linear ...

During the course of operation, businesses accumulate all kinds of data such as numbers related to sales performance and profit, and information about clients. Companies often seek out employees with ...