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...
Subscribe
- Never miss a story with notifications
- Gain full access to our premium content
- Browse free from up to 5 devices at once
Must read