The increasing interest in Support Vector Machines (SVMs) over the past 15 years is
described. Methods are illustrated using simulated case studies, and 4 experimental case …

We present an algorithmic framework for learning local causal structure around target
variables of interest in the form of direct causes/effects and Markov blankets applicable to …

The ability to nondestructively image and automatically phenotype complex root systems,
like those of rice (Oryza sativa), is fundamental to identifying genes underlying root system …

Background The goal of class prediction studies is to develop rules to accurately predict the
class membership of new samples. The rules are derived using the values of the variables …

Gene selection aims at identifying a (small) subset of informative genes from the initial data
in order to obtain high predictive accuracy for classification. Gene selection can be …

Feature selection often aims to select a compact feature subset to build a pattern classifier
with reduced complexity, so as to achieve improved classification performance. From the …

Heterogeneity is a characteristic feature of all populations of living organisms. Here we
make an attempt to validate a single-cell mass spectrometric method for detection of …

Brain tumor diagnosis is a very crucial task. This system provides an efficient and fast way
for diagnosis of the brain tumor. Proposed system consists of multiple phases. First phase …

Trace gas exchange of N2O, NO, and CO2 between soil and the atmosphere was measured
with high temporal resolution for 5 years (2004–2008) at the Höglwald Forest, Germany …

Support Vector Machines, a new generation learning system based on recent advances in
statistical learning theory deliver state-of-the-art performance in real-world applications such …