Dimensionality Reduction: 편집 역사

2024년 12월 2일 (월)

• 최신이전 06:092024년 12월 2일 (월) 06:09‎ Dendrogram 토론 기여‎ 3,754 바이트 +3,754‎ 새 문서: '''Dimensionality Reduction''' is a technique used in machine learning and data analysis to reduce the number of features (dimensions) in a dataset while preserving as much relevant information as possible. It simplifies data visualization, reduces computational costs, and helps mitigate the curse of dimensionality. ==Importance of Dimensionality Reduction== Dimensionality reduction is crucial for the following reasons: *'''Improves Model Performance:''' Reducing irrelevant or r... 태그: 시각 편집