My Learning Cart
?
Categories
Account

Which of the following is a common technique used in feature selection?

₹0.0
Login to Download
  • 📥 Instant PDF Download
  • ♾ Lifetime Access
  • 🛡 Secure & Original Content

What’s inside this PDF?

Question: Which of the following is a common technique used in feature selection?

Options:

  1. Principal Component Analysis (PCA)
  2. K-Means Clustering
  3. Support Vector Machines (SVM)
  4. Random Forest Regression

Correct Answer: Principal Component Analysis (PCA)

Solution: 

Principal Component Analysis (PCA) is a dimensionality reduction technique that can also be used for feature selection by identifying the most important features.

Which of the following is a common technique used in feature selection?

Practice Questions

Q1
Which of the following is a common technique used in feature selection?
  1. Principal Component Analysis (PCA)
  2. K-Means Clustering
  3. Support Vector Machines (SVM)
  4. Random Forest Regression

Questions & Step-by-Step Solutions

Which of the following is a common technique used in feature selection?
  • Step 1: Understand what feature selection means. It is the process of choosing important features (variables) from your data that help in making predictions.
  • Step 2: Learn about Principal Component Analysis (PCA). PCA is a method that reduces the number of features while keeping the most important information.
  • Step 3: Recognize that PCA can help in feature selection by identifying which features contribute the most to the data's variance.
  • Step 4: Conclude that PCA is a common technique used in feature selection because it simplifies the data while retaining essential features.
No concepts available.
Soulshift Feedback ×

On a scale of 0–10, how likely are you to recommend The Soulshift Academy?

Not likely Very likely
Home Practice Performance eBooks