In many applications of information systems learning algorithms have to act in dynamic
environments where data are collected in the form of transient data streams. Compared to …

Activity detection and classification using different sensor modalities have emerged as
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …

The change detection and land use and land cover (LULC) maps are more important
powerful forces behind numerous ecological systems and fallow land. The current research …

This is a book on data analysis with a specific focus on the practice of predictive modeling.
The term predictive modeling may stir associations such as machine learning, pattern …

Ensemble methods that train multiple learners and then combine them to use, with Boosting
and Bagging as representatives, are well-known machine learning approaches. It has …

A current focus of intense research in pattern classification is the combination of several
classifier systems, which can be built following either the same or different models and/or …

Predicting Alzheimer's disease (AD) progression is crucial for improving the management of
this chronic disease. Usually, data from AD patients are multimodal and time series in …

Twitter is a microblogging site in which users can post updates (tweets) to friends (followers).
It has become an immense dataset of the so-called sentiments. In this paper, we introduce …

The primary goal of pattern recognition is supervised or unsupervised classification. Among
the various frameworks in which pattern recognition has been traditionally formulated, the …

This paper introduces the problem of combining multiple partitionings of a set of objects into
a single consolidated clustering without accessing the features or algorithms that …