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EVRI-thing You Need to Know About MLR, Ridge, LASSO and ElasticNet

August 18, 2022

First developed more than 100 years ago by Francis Galton and then Karl Pearson, Multiple Linear Regression (MLR) aka Ordinary Least Squares (OLS) is ubiquitous. For problems with relatively few independent variables it usually works as intended. However there are many instances where the method goes wrong and gives non-sensical regression coefficients and sub-optimal prediction performance. This is generally a result of poor conditioning in the predictor variables, i.e. instances where the predictor variables are strongly correlated or redundant. Of course, data sets where there are more variables than observations also present problems for MLR.

Our webinar series continues on Thursday, August 18 with “EVRI-thing You Need to Know About MLR, Ridge, LASSO and ElasticNet.” Join Eigenvector President Barry M. Wise along with Principal Consultant and Data Scientist Manny Palacios as they discuss MLR’s shortcomings and several modifications used to improve its performance.

In this webinar we’ll discuss:

  • Multiple Linear Regression (MLR)
  • Why MLR goes bad
  • Ridge Regression
  • Least Absolute Shrinkage and Selection Operator: LASSO
  • Combining Ridge and LASSO: ElasticNet
  • Some examples

Register for “EVRI-thing You Need to Know About MLR, Ridge, LASSO and ElasticNet” through your existing Eigenvector account, or create one. The webinar is free, but you must register to attend. Find the webinar near the bottom of the page under the “Purchase” tab.

A question and answer session will follow the webinar. Don’t miss your chance to quiz Manny, Barry and the Eigen-Guys about how to make MLR behave by using the new tools for Ridge Regression, LASSO and ElasticNet found in the upcoming PLS_Toolbox and Solo 9.1.

Reserve your seat today. The webinar will be live on Thursday, August 18, at 7:00am PDT, (that’s 16:00 CEST). We will send you a WebEx invitation the day before the webinar. We hope you can attend live, but if you sign up and can’t make it, we’ll send you a link to view the recording the day after the webinar.