Feature Importance
Machine Learning
The process of identifying and extracting distinctive characteristics from data for further analysis.
Detailed Explanation
Feature extraction involves transforming raw data into informative attributes that enhance model performance. By identifying key patterns or characteristics, it simplifies complex data, reduces dimensionality, and improves accuracy in tasks like classification or regression. This process is crucial for making machine learning algorithms more efficient and effective in understanding underlying data structures.
Use Cases
- •Use case: Improving image classification accuracy by extracting key features like edges and textures from raw images.
Related Terms
Other terms in the Machine Learning category