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.

Linear regression is a statistical method used to understand the relationship between an outcome variable and one or more explanatory variables. It works by fitting a regression line through the ...

The first five values on each line are the x predictors. The last value on each line is the target y variable to predict. The demo creates a linear support vector regression model, evaluates the model ...

The classic introduction to X-Y plots is the Lissajous plot. Two sine waves are plotted against each other. For sine wave of the same frequency the plot is used to measure the phase difference between ...

The Data Science Lab Regression Using PyTorch New Best Practices, Part 2: Training, Accuracy, Predictions Dr. James McCaffrey of Microsoft Research updates regression techniques and best practices ...

In this article we study nonparametric regression quantile estimation by kernel weighted local linear fitting. Two such estimators are considered. One is based on localizing the characterization of a ...

Liang & Zeger (1986) introduced a generalised estimating equations approach based on a `working' correlation matrix to obtain consistent and efficient estimators of regression parameters in the class ...

Objective To estimate the efficacy of exercise on depressive symptoms compared with non-active control groups and to determine the moderating effects of exercise on depression and the presence of ...