At the current state of development of chemistry, it appears easier to synthesize a compound
with a definite chemical structure than with a certain required property. Usually, reaction …

Since the pioneering works of Kaliszan (R. Kaliszan, Quantitative Structure–
Chromatographic Retention Relationships, Wiley, New York, 1987; and R. Kaliszan …

The standard 2-norm SVM is known for its good performance in two-In this paper, we
consider the 1-norm SVM. We class classi£ cation. argue that the 1-norm SVM may have …

Offering a fundamental basis in kernel-based learning theory, this book covers both
statistical and algebraic principles. It provides over 30 major theorems for kernel-based …

We describe a methodology for performing variable ranking and selection using support
vector machines (SVMs). The method constructs a series of sparse linear SVMs to generate …

In order to on-line control the quality of industrial products, often spectroscopic methods are
used in combination with regression tools. Partial Least Squares (PLS) is the most used …

The standard L2-norm support vector machine (SVM) is a widely used tool for classification
problems. The L1-norm SVM is a variant of the standard L2-norm SVM, that constrains the …

The observation that some properties attributed to atoms and functional groups are
transferable from one molecule to another has played a key role in the development of …

One of the most extended subfields of chemometrics, at least by considering the number of
publications and interested researchers, is QSAR/QSPR. During the time, various improved …

Support vector machines (SVMs) were used to develop QSAR models that correlate
molecular structures to their toxicity and bioactivities. The performance and predictive ability …