Principal Component Analysis (PCA)

What is Principal Component Analysis?

Principal Component Analysis means pCA reduces the number of features while trying to keep the most important information.

In real programs, this topic helps in reducing many features. Learn the idea first, then type the program yourself and compare the output.

Why should you learn this?

• It is useful for reducing many features.
• It connects with visualising high-dimensional data.
• It improves your ability to read, write and debug Python programs.

Important Terms

These terms are used directly in this lesson. Understand them before memorising the code.

Syntax / Basic Pattern

The simple pattern is: prepare data, apply the concept, then show the result.

from sklearn.decomposition import PCA
X = [[2, 4, 6], [3, 6, 9], [4, 8, 12], [5, 10, 15]]
pca = PCA(n_components=1)
X_new = pca.fit_transform(X)
print(X_new)

Complete Example Program

from sklearn.decomposition import PCA

X = [[2, 4, 6], [3, 6, 9], [4, 8, 12], [5, 10, 15]]

pca = PCA(n_components=1)
X_new = pca.fit_transform(X)
print(X_new)

Expected Output

Program Explanation

• from sklearn.decomposition import PCA imports ready-made features from a module/library.
• X = [[2, 4, 6], [3, 6, 9], [4, 8, 12], [5, 10, 15]] stores a value in X.
• pca = PCA(n_components=1) stores a value in pca.
• X_new = pca.fit_transform(X) stores a value in X_new.
• print(X_new) displays information or calculated result on the screen.

Where will you use it?

• Reducing many features.
• Visualising high-dimensional data.
• Removing redundant information.

Common Mistakes

• Training and testing the model on the same data.
• Using an algorithm without understanding the input features.
• Reporting only accuracy without checking actual mistakes and limitations.

Practice Tasks

1. Type the program in pca.py and run it.
2. Change input values or sample data and observe the new output.
3. Create one example related to reducing many features.
4. Write 5 lines explaining the logic in your own words.

Summary

Principal Component Analysis is not a theory-only topic. You should be able to explain the meaning, write the example, run it successfully, and use it in a small practical program.