An up-to-date, self-contained introduction to a state-of-the-art machine learning approach,
Ensemble Methods: Foundations and Algorithms shows how these accurate methods are …

Neural networks have been successfully employed in various domains such as
classification, regression and clustering, etc. Generally, the back propagation (BP) based …

“Radiomics” refers to the extraction and analysis of large amounts of advanced quantitative
imaging features with high throughput from medical images obtained with computed …

GABA interneurons play a critical role in higher brain functions. Astrocytic glial cells interact
with synapses throughout the whole brain and are recognized as regulatory elements of …

The evaluation of clustering algorithms is intrinsically difficult because of the lack of objective
measures. Since the evaluation of clustering algorithms normally involves multiple criteria, it …

The self-organizing map (SOM) is an automatic data-analysis method. It is widely applied to
clustering problems and data exploration in industry, finance, natural sciences, and …

Membership Inference Attack (MIA) determines the presence of a record in a machine
learning model's training data by querying the model. Prior work has shown that the attack is …

Twitter is among the fastest‐growing microblogging and online social networking services.
Messages posted on Twitter (tweets) have been reporting everything from daily life stories to …

The validation of the results obtained by clustering algorithms is a fundamental part of the
clustering process. The most used approaches for cluster validation are based on internal …

Face attribute estimation has many potential applications in video surveillance, face
retrieval, and social media. While a number of methods have been proposed for face …