Artificial Intelligence (AI) is undoubtedly one of the most actively debated technologies,
providing auspicious opportunities to contribute to individuals' well-being, the success and …

Classification is the key and most widely studied paradigm in machine learning community.
The selection of appropriate classification algorithm for a particular problem is a challenging …

Meta-learning, or learning to learn, is the science of systematically observing how different
machine learning approaches perform on a wide range of learning tasks, and then learning …

With the continuous and vast increase in the amount of data in our digital world, it has been
acknowledged that the number of knowledgeable data scientists can not scale to address …

Metalearning attracted considerable interest in the machine learning community in the last
years. Yet, some disagreement remains on what does or what does not constitute a …

Automated recommendation of machine learning algorithms is receiving a large deal of
attention, not only because they can recommend the most suitable algorithms for a new task …

This paper tackles the issue of objective performance evaluation of machine learning
classifiers, and the impact of the choice of test instances. Given that statistical properties or …

Meta-learning is increasingly used to support the recommendation of machine learning
algorithms and their configurations. These recommendations are made based on meta-data …

Objective Manual evaluation of machine learning algorithms and selection of a suitable
classifier from the list of available candidate classifiers, is highly time consuming and …

Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …