The Significance of Train-Validation-Test Split in Machine Learning

Introduction

In the realm of machine learning, the adage “garbage in, garbage out” succinctly captures the essence of data quality’s profound impact on model performance. One of the quintessential techniques that stands as a sentinel against subpar models is the train-validation-test split. This fundamental process of partitioning a dataset into distinct subsets serves as the bedrock upon which the edifice of model development, evaluation, and generalization is erected.