In the example below, I use an e-commerce data set to build a regression model. I also explain how to determine if the model reveals anything statistically significant, as well as how outliers may ...

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

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...

We develop a new multiple imputation approach for M-regression models with censored covariates. Instead of specifying parametric likelihoods, our method imputes the censored covariates by their ...

Learn how to do time series regression using a neural network, with 'rolling window' data, coded from scratch, using Python.

A sequential regression or chained equations imputation approach uses a Gibbs sampling-type iterative algorithm that imputes the missing values using a sequence of conditional regression models. It is ...

Using Kalman equations, we derive straightforward formulas for the total imputation variance for several imputation methods commonly used in regression analysis and (un)equal probability sampling ...