#knowledgediscovery

‘These types of dimensionality techniques [PCA and ICA methods for finding parameter combinations within a dataset], can be useful for identifying classes of objects, for detecting rare or outlying objects, and for constructing compact representations of the distribution of observed objects. One potential weakness of dimensionality reduction algorithms is that the components are defined statistically, and as such have no guarantee of reflecting true physical aspects of the systems being observed. Because of this, one must be careful when making physical inferences from such results.’

We have BIG news to share with you. We won the bid to host the 2017 Conference on Knowledge Discovery and Data Mining, and we can`t wait to welcome over 1,000 of the world's leading edge researchers and practitioners in big data to our city!