Benchmarking pattern recognition, machine learning and data mining methods commonly relies on real-world data sets. However, there are some disadvantages in using real-world data....
Janick V. Frasch, Aleksander Lodwich, Faisal Shafa...
In many applications, classifiers need to be built based on multiple related data streams. For example, stock streams and news streams are related, where the classification patter...
Yabo Xu, Ke Wang, Ada Wai-Chee Fu, Rong She, Jian ...
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Data missing is a common problem in database query processing, which can cause bias or lead to inefficient analyses, and this problem happens more often in sensor databases. The re...