The growing prevalence of resistance to antibiotics motivates the search for new
antibacterial agents. Antimicrobial peptides are a diverse class of well-studied membrane …

This paper explores feature scoring and selection based on weights from linear
classification models. It investigates how these methods combine with various learning …

Dimensionality reduction is a commonly used step in machine learning, especially when
dealing with a high dimensional space of features. The original feature space is mapped …

Credit risk evaluation is one of the most important topics in the field of financial risk
management. Due to recent financial crises and regulatory concern of Basel II, credit risk …

The free text in electronic health records (EHRs) conveys a huge amount of clinical
information about health state and patient history. Despite a rapidly growing literature on the …

In this paper, we review two techniques for topic discovery in collections of text documents
(Latent Semantic Indexing and K-Means clustering) and present how we integrated them …

The dangers of the construction industry due to the risk of fatal hazards, such as falling from
extreme heights, being struck by heavy equipment or materials, and the possibility of …

Forecasting the creditworthiness of customers is a central issue of banking activity. This task
requires the analysis of large datasets with many variables, for which machine learning …

The ADHD-200 Global Competition provides an excellent opportunity for building diagnostic
classifiers of Attention-Deficit/Hyperactivity Disorder (ADHD) based on resting-state …

MicroRNAs have been long considered synthesized endogenously until very recent
discoveries showing that human can absorb dietary microRNAs from animal and plant …