PCA
Explore Principal Component Analysis to reduce the number of features in datasets by extracting key uncorrelated components. Understand why PCA is essential for simplifying data and improving machine learning models, and learn to apply it using scikit-learn's PCA module with practical coding exercises.
We'll cover the following...
We'll cover the following...
Chapter Goals:
- Learn about principal component analysis and why it's used
A. Dimensionality reduction
Most datasets contain a large number of features, some of which are redundant or not informative. For example, in a dataset of basketball statistics, the total points and points per game for a player will (most of the time) tell the same story about the player's scoring prowess.
When a dataset contains these types of correlated numeric features, we can perform ...