Current Slide
Small screen detected. You are viewing the mobile version of SlideWiki. If you wish to edit slides you will need to use a larger device.
Data Reduction 1: Dimensionality Reduction
- Curse of dimensionality
- When dimensionality increases, data becomes increasingly sparse
- Density and distance between points, which is critical to clustering, outlier analysis, becomes less meaningful
- The possible combinations of subspaces will grow exponentially
- Dimensionality reduction
- Avoid the curse of dimensionality
- Help eliminate irrelevant features and reduce noise
- Reduce time and space required in data mining
- Allow easier visualization
- Dimensionality reduction techniques
- Wavelet transforms
- Principal Component Analysis
- Supervised and nonlinear techniques (e.g., feature selection)
Speaker notes:
Content Tools
Tools
Sources (0)
Tags (0)
Comments (0)
History
Usage
Questions (0)
Playlists (0)
Quality
Sources
There are currently no sources for this slide.