Effective and unsupervised fractal-based feature selection for very large datasets: removing linear and non-linear attribute correlations
Given a very large dataset of moderate-to-high dimensionality, how to mine useful patterns from it? In such cases, dimensionality reduction is essential to overcome the well-known curse of dimensionality. Although there exist algorithms to reduce the dimensionality of Big Data, unfortunately, th...
| Main Author: | |
|---|---|
| Other Authors: | |
| Language: | English |
| Published: |
Universidade de São Paulo
2017
|
| Subjects: | |
| Online Access: | http://www.teses.usp.br/teses/disponiveis/55/55134/tde-17112017-154451/ |