We report on three distinct experiments that provide new valuable insights into learning algorithms and datasets. We first describe two effective meta-features that significantly ...
This paper reports the results of feature reduction in the analysis of a population based dataset for which there were no specific target variables. All attributes were assessed a...
Naive Bayes models have been widely used for clustering and classification. However, they are seldom used for general probabilistic learning and inference (i.e., for estimating an...
Estimating the optimal number of clusters for a dataset is one of the most essential issues in cluster analysis. An improper pre-selection for the number of clusters might easily ...
Given the ubiquity of time series data, the data mining community has spent significant time investigating the best time series similarity measure to use for various tasks and dom...
Qiang Zhu 0002, Gustavo E. A. P. A. Batista, Thana...