Which of the following is NOT a common technique for feature selection?
Practice Questions
Q1
Which of the following is NOT a common technique for feature selection?
Recursive Feature Elimination
Principal Component Analysis
Random Forest Importance
Gradient Descent
Questions & Step-by-Step Solutions
Which of the following is NOT a common technique for feature selection?
Step 1: Understand what feature selection means. Feature selection is the process of choosing the most important variables (features) from your data to use in a model.
Step 2: Identify common techniques for feature selection. Some common techniques include filter methods, wrapper methods, and embedded methods.
Step 3: Recognize what Gradient Descent is. Gradient Descent is an optimization algorithm used to minimize the error in a model by adjusting the model's parameters.
Step 4: Compare Gradient Descent with feature selection techniques. Since Gradient Descent is used for optimization and not for selecting features, it is NOT a feature selection technique.
Step 5: Conclude that the answer to the question is Gradient Descent.
