The histological assessment of human tissue has emerged as the key challenge for
detection and treatment of cancer. A plethora of different data sources ranging from tissue …

Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …

In the last two decades, machine learning research and practice has focused on batch
learning, usually with small datasets. Nowadays there are applications in which the data are …

We propose and illustrate a method for developing algorithms that can adaptively learn from
data streams that drift over time. As an example, we take Hoeffding Tree, an incremental …

The ability to restructure a decision tree efficiently enables a variety of approaches to
decision tree induction that would otherwise be prohibitively expensive. Two such …

In this paper we study the problem of constructing accurate decision tree models from data
streams. Data streams are incremental tasks that require incremental, online, and any-time …

Cloud and Fog computing has emerged as a promising paradigm for the Internet of things
(IoT) and cyber–physical systems (CPS). One characteristic of CPS is the reciprocal …

Timely and accurate mapping of leaf area index (LAI) in vineyards plays an important role for
management choices in precision agricultural practices. However, only a little work has …

In this paper we study the problem of constructing accurate decision tree models from data
streams. Data streams are incremental tasks that require incremental, online, and any-time …

Knowledge about computer users is very beneficial for assisting them, predicting their future
actions or detecting masqueraders. In this paper, a new approach for creating and …