Ensemble diversity is an important characteristic of Multiple Classifier Systems (MCS), which
aim at improving the overall performance of a classification system by combining the …

Although vegetation index time series from optical images are widely used for crop mapping,
it remains difficult to obtain sufficient time-series data because of satellite revisit time and …

Dynamic selection techniques select a subset of the classifiers from a pool according to their
perceived competence in labeling each given query instance in particular. To do so, most …

The ensemble methods are meta-algorithms that combine several base machine learning
techniques to produce one optimal predictive model. Many existing committees of classifiers …

The study was to investigate the diagnostic value of ultrasound based on the random forest
segmentation algorithm for dry eye disease and the relationship between dry eye degree …

Dynamic selection techniques select a subset of the classifiers from a pool according to their
perceived competence in labeling each given query instance in particular. To do so, most …

Human resource management has a significant role in influencing organizational
performance. As a company that seeks to increase objectivity and decision making that …

Dynamic selection techniques are based on the idea that the classifiers from an ensemble
are experts in different areas of the feature space. As such, they attempt to single out only …

Artificial intelligence and machine learning systems became a part of every field of our lives
and are still gaining in popularity. It did not only take over the world of science, but also …