Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently however, we have been approached by Texas Commiss...
Kun Zhang, Wei Fan, Xiaojing Yuan, Ian Davidson, X...
Abstract. An application of the recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling of time series data is presented. We use G...
Much work on skewed, stochastic, high dimensional, and biased datasets usually implicitly solve each problem separately. Recently, we have been approached by Texas Commission on En...
High dimensional data visualization is critical to data analysts since it gives a direct view of original data. We present a method to visualize large amount of high dimensional d...