In machine learning, features are the pieces of information that help a computer make decisions.
You can think of them as the clues the computer looks at when trying to learn something.
For example, if you want a computer to predict the price of a house, the features might include
Feature selection is the process of choosing which of these clues are the most useful.
Not all features help the computer learn — some may be irrelevant or even confusing.
By selecting only the best features, we make the model faster, simpler, and often more accurate.
Make a copy of the worksheet. Move it into your Theme A4 folder.
Follow the instructions and complete the tasks.
Make a new entry in the Journal section of the booklet.
Did you discover anything new today? Do you have questions in your mind that you want answers to?
Make these notes in your journal.
Machine Learning
Supervised Learning
Unsupervised Learning
Labels
Training
Training data
Test data
Features
Machine Learninglabels Supervised learning Unsupervised learning features model training data trainingtest data