The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

That said, much real-life data is mostly linearly separable, and in such situations logistic regression can work well. Logistic regression can in principle be modified to handle problems where the ...

I use Python 3 and Jupyter Notebooks to generate plots and equations with linear regression on Kaggle data. I checked the correlations and built a basic machine learning model with this dataset.

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 behind the linear regression in python.

When multiple variables are associated with a response, the interpretation of a prediction equation is seldom simple.

First, multiple linear regression models are considered and the design matrices are allowed to be different. Second, the predictor variables are either unconstrained or constrained to finite intervals ...

In this paper, we consider the problem of determining the number of structural changes in multiple linear regression models via group fused Lasso. We show that with probability tending to one, our ...