Data from spectrophotometers form vectors of a large number of exploitable variables.
Building quantitative models using these variables most often requires using a smaller set of …

This paper introduces a new methodology to perform feature selection in multi-label
classification problems. Unlike previous works based on the χ 2 statistics, the proposed …

Nondestructive and rapid estimation of soil total nitrogen (TN) content by using near-infrared
spectroscopy plays a crucial role in agriculture. The obtained original spectrum, however …

This paper proposes the use of mutual information for feature selection in multi-label
classification, a surprisingly almost not studied problem. A pruned problem transformation …

In this work, different approaches for variable selection are studied in the context of near-
infrared (NIR) multivariate calibration of textile. First, a model-based regression method is …

Variable selection is of major interest for NIR calibration, either as a feature selection or for
the design of multi-wavelength devices. Some dedicated methods have been developed in …

This paper presents two methodologies for monitoring the service condition of diesel-engine
lubricating oils on the basis of infrared spectra. In the first approach, oils samples are …

Crop growth in different periods influences the final yield. This study started from the
agronomic mechanism of yield formation and aimed to extract useful spectral characteristics …

Spectrophotometry is more and more often the method of choice not only in analysis of (bio)
chemical substances, but also in the identification of physical properties of various objects …

Feature extraction and selection are important issues in soft sensing and complex nonlinear
system modeling. In this paper, a new feature extraction and selection approach based on …