In recent years, there has been an exponential growth in the number of complex documents
and texts that require a deeper understanding of machine learning methods to be able to …

Classification problems involving multiple classes can be addressed in different ways. One
of the most popular techniques consists in dividing the original data set into two-class …

In castration-resistant prostate cancer (CRPC), the loss of androgen receptor (AR)
dependence leads to clinically aggressive tumors with few therapeutic options. We used …

We perform a large-scale RNA sequencing study to experimentally identify genes that are
downregulated by 25 miRNAs. This RNA-seq dataset is combined with public miRNA target …

Some recent studies have shown that machine learning can achieve higher predictive
accuracy than logit models. However, existing studies rarely examine behavioral outputs …

In recent years, airborne and spaceborne hyperspectral imaging systems have advanced in
terms of spectral and spatial resolution, which makes the data sets they produce a valuable …

Shotgun metagenomic analysis of the human associated microbiome provides a rich set of
microbial features for prediction and biomarker discovery in the context of human diseases …

We propose a data mining (DM) approach to predict the success of telemarketing calls for
selling bank long-term deposits. A Portuguese retail bank was addressed, with data …

Ordinal regression problems are those machine learning problems where the objective is to
classify patterns using a categorical scale which shows a natural order between the labels …

High-performance batteries greatly benefit from accurate, early predictions of future capacity
loss, to advance the management of the battery and sustain desirable application-specific …