How-To Geek on MSN

How to run R-style linear regressions in Python the easy way

If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can ...
Visual Studio Magazine

Kernel Ridge Regression with Cholesky Inverse Training Using C#

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's bank savings account balance based on their age, years of work ...
JSTOR Daily

Testing for Lack of Fit in Inverse Regression: With Applications to Biophotonic Imaging

This is a preview. Log in through your library . Abstract We propose two test statistics for use in inverse regression problems Y = Kθ + ε, where K is a given linear operator which cannot be ...
JSTOR Daily

Sparse Sliced Inverse Regression

Sliced inverse regression (SIR) is an innovative and effective method for dimension reduction and data visualization of high-dimensional problems. It replaces the original variables with ...
Visual Studio Magazine

Linear Ridge Regression Using C#

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, number of bedrooms, ...
American Enterprise Institute

Goldilocks vs. Robin Hood: Using Shape-Constrained Regression to Evaluate U-Shaped (or Inverse U-Shaped) Theories in Data

sciences. As a result of this widespread interest in identifying non-monotonic relationships in data and the well-known problems with standard parametric approaches based on quadratic regression ...
Investopedia

Regression Basics for Business Analysis

Suzanne is a content marketer, writer, and fact-checker. She holds a Bachelor of Science in Finance degree from Bridgewater State University and helps develop content strategies. If you've ever ...