Interface administrators, Administrators (Semantic MediaWiki), Curators (Semantic MediaWiki), Editors (Semantic MediaWiki), Suppressors, Administrators
7,785
edits
Feature engineering: Difference between revisions
no edit summary
(Created page with "==Introduction== Feature engineering is a critical process in machine learning that involves selecting, extracting, and transforming relevant features or variables from raw data to improve the accuracy and performance of machine learning models. Feature engineering is a complex and challenging process that requires domain knowledge, creativity, and expertise in data manipulation techniques. The objective of feature engineering is to transform raw data into a more suitabl...") |
No edit summary |
||
| Line 1: | Line 1: | ||
==Introduction== | ==Introduction== | ||
Feature engineering is a critical process in machine learning that involves selecting, extracting, and transforming relevant | [[Feature engineering]] is a critical process in [[machine learning]] that involves selecting, extracting, and transforming relevant [[feature]]s or variables from raw [[data]] to improve the accuracy and performance of [[machine learning models]]. Feature engineering is a complex and challenging process that requires domain knowledge, creativity, and expertise in data manipulation techniques. The objective of feature engineering is to transform raw data into a more suitable and informative representation that can be easily understood by machine learning models. | ||
Note that feature engineering is sometimes called '''feature extraction'''. | |||
==What are features in machine learning?== | ==What are features in machine learning?== | ||