To improve model performance by reducing overfitting
To create new features from existing ones
To visualize the data
Questions & Step-by-Step Solutions
What is the main goal of feature selection?
Step 1: Understand that feature selection is a process used in machine learning.
Step 2: Recognize that features are the input variables used to make predictions.
Step 3: Know that the main goal of feature selection is to choose the most important features.
Step 4: Realize that by selecting important features, we can improve the model's performance.
Step 5: Understand that reducing the number of features helps to prevent overfitting, which is when a model learns too much from the training data and performs poorly on new data.
Step 6: Finally, remember that a good feature selection helps the model to generalize better to unseen data.
