How to Evaluate Machine Learning Algorithms with R
Last Updated on December 13, 2019
What algorithm should you use on your dataset?
This is the most common question in applied machine learning. It’s a question that can only be answered by trial and error, or what I call: spot-checking algorithms.
In this post you will discover how to spot check algorithms on a dataset using R. Including the selection of test options, evaluation metrics, and algorithms.
You can use the code in this post as a template for spot checking machine learning algorithms on your own problems.
Kick-start your project with my new book Machine Learning Mastery With R, including step-by-step tutorials and the R source code files for all examples.
Let’s get started.
Evaluate Machine Learning Algorithms with R
Photo by Brian Townsley, some rights reserved.
Best Algorithm For a Problem
You want the most accurate model for your dataset. That is the goal of predictive modeling.
No one can tell you what algorithm to use on your dataset to get the best results. If you or
To finish reading, please visit source site