All 7 Training vs Testing Data questions
More in Training vs Testing Data
What is Training vs Testing Data How does Training vs Testing Data work What are the key parts or types of Training vs Testing Data What are common mistakes to avoid with Training vs Testing Data What is a real world example of Training vs Testing Data What are best practices for Training vs Testing Data
Advertisement
Back to results for “Machine Learning Fundamentals”
Machine Learning Fundamentals › Training vs Testing Data

Why is Training vs Testing Data important in Machine Learning Fundamentals

Beginner

Answer

Separating training and testing data is important because it shows whether a model actually learned useful patterns or just memorized the training examples. Without this split you cannot trust the reported accuracy.
Real-world example A bank builds a loan approval model on data from the last five years and tests it on the most recent six months of applications to see how it would have performed in practice.

Common follow-ups: What is a validation set, What is cross validation, What is overfitting

Machine Learning Fundamentals Deep Learning Supervised & Unsupervised Learning
All 7 Training vs Testing Data questions