Cross-Validation Types and When to Use It

A better way to test your models

Overview

Building machine learning models is a great process that includes several steps

1. Collection of data
2. Data Preparation & Preprocessing
3. Expletory Data Analysis
4. Feature Engineering and Selection
5. Model Building and Evaluation

• Cross-Validation is one of the most important parts of Model Building and Evaluation.
• Before experimenting with Cross-Validation, let’s see what it is and why we should worry about using it.

Why Cross Validation?

• Let’s say we have 10000 rows ( …

crossvalidation data science machine learning model-evaluation types validation