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Machine Learning Tutorials

Machine Learning Tutorials

Principal Components Analysis in R: Step-by-Step Example

Principal components analysis, often abbreviated PCA, is an unsupervised machine learning technique that seeks to find principal components – linear combinations of the original...
Machine Learning Tutorials

An Introduction to Bagging in Machine Learning

When the relationship between a set of predictor variables and a response variable is linear, we can use methods like multiple linear regression to...
Machine Learning Tutorials

An Introduction to Classification and Regression Trees

When the relationship between a set of predictor variables and a response variable is linear, methods like multiple linear regression can produce accurate predictive...
Machine Learning Tutorials

A Simple Introduction to Boosting in Machine Learning

Most supervised machine learning algorithms are based on using a single predictive model like linear regression, logistic regression, ridge regression, etc.  Methods like bagging and...
Machine Learning Tutorials

A Simple Introduction to Random Forests

When the relationship between a set of predictor variables and a response variable is highly complex, we often use non-linear methods to model the...
Advanced Regression Models in Machine Learning

An Introduction to Multivariate Adaptive Regression Splines

When the relationship between a set of predictor variables and a response variable is linear, we can often use linear regression, which assumes that...
Advanced Regression Models in Machine Learning

An Introduction to Polynomial Regression

When we have a dataset with one predictor variable and one response variable, we often use simple linear regression to quantify the relationship between the...
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