Dimension Reduction in Machine Learning
An Introduction to Partial Least Squares
One of the most common problems that you’ll encounter in machine learning is multicollinearity. This occurs when two or more predictor variables in a...
Dimension Reduction in Machine Learning
An Introduction to Principal Components Regression
One of the most common problems that you’ll encounter when building models is multicollinearity. This occurs when two or more predictor variables in a...
Machine Learning Tutorials
Introduction to Lasso Regression
In ordinary multiple linear regression, we use a set of p predictor variables and a response variable to fit a model of the form:
Y =...
Machine Learning Tutorials
Introduction to Ridge Regression
In ordinary multiple linear regression, we use a set of p predictor variables and a response variable to fit a model of the form:
Y =...
Machine Learning Tutorials
What is Stepwise Selection? (Explanation & Examples)
In the field of machine learning, our goal is to build a model that can effectively use a set of predictor variables to predict...
Machine Learning Tutorials
Best Subset Selection in Machine Learning (Explanation & Examples)
In the field of machine learning, we’re often interested in building models using a set of predictor variables and a response variable. Our goal...
How to Assess Model Fit in Machine Learning
What is Overfitting in Machine Learning? (Explanation & Examples)
In the field of machine learning, we often build models so that we can make accurate predictions about some phenomenon.
For example, suppose we want...
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