Add to ORKGThis paper aims to provide a unified framework for the evaluation and comparison of the many emergent meta-mining techniques. This framework is illustrated on the case study of the meta-learning problem in a large scale experiment. The results of this experiment are then explored through hypothesis testing in order to provide insight regarding the performance of the different meta-learning schemes, advertising the potential of our approach regarding meta-level knowledge discovery
: Meta-learning is a field of learning that aims at addressing the challenges of conventional machin...
JAM is a powerful and portable agent-based distributed data mining system that employs meta-learning...
Many studies in machine learning try to in-vestigate what makes an algorithm succeed or fail on cert...
Ce texte est un aperçu de "Meta-Mining Evaluation Framework : A large scale proof of concept on Meta...
This paper describes the use of meta-learning in the area of data mining. It describes the problems ...
While a valid intellectual challenge in its own right, meta-learning finds its real raison d’être in...
In this chapter, we provide a survey of the various architectures that have been developed, or simpl...
Meta-learning, or learning to learn, is the science of systematically observing how different machin...
In the paper, we propose a new approach to applying meta-learning concepts to parallel data mining. ...
This chapter describes a principled approach to meta-learning that has three distinctive features. F...
Many studies in machine learning try to investigate what makes an algorithm succeed or fail on certa...
The field of artificial intelligence has been throughout its history repeatedly inspired by human co...
There is no free lunch, no single learning algorithm that will outperform other algorithms on all da...
Many studies in machine learning try to investigate what makes an algorithm succeed or fail on certa...
Meta-learning is an efficient approach in the field of machine learning, which involves multiple cla...
: Meta-learning is a field of learning that aims at addressing the challenges of conventional machin...
JAM is a powerful and portable agent-based distributed data mining system that employs meta-learning...
Many studies in machine learning try to in-vestigate what makes an algorithm succeed or fail on cert...
Ce texte est un aperçu de "Meta-Mining Evaluation Framework : A large scale proof of concept on Meta...
This paper describes the use of meta-learning in the area of data mining. It describes the problems ...
While a valid intellectual challenge in its own right, meta-learning finds its real raison d’être in...
In this chapter, we provide a survey of the various architectures that have been developed, or simpl...
Meta-learning, or learning to learn, is the science of systematically observing how different machin...
In the paper, we propose a new approach to applying meta-learning concepts to parallel data mining. ...
This chapter describes a principled approach to meta-learning that has three distinctive features. F...
Many studies in machine learning try to investigate what makes an algorithm succeed or fail on certa...
The field of artificial intelligence has been throughout its history repeatedly inspired by human co...
There is no free lunch, no single learning algorithm that will outperform other algorithms on all da...
Many studies in machine learning try to investigate what makes an algorithm succeed or fail on certa...
Meta-learning is an efficient approach in the field of machine learning, which involves multiple cla...
: Meta-learning is a field of learning that aims at addressing the challenges of conventional machin...
JAM is a powerful and portable agent-based distributed data mining system that employs meta-learning...
Many studies in machine learning try to in-vestigate what makes an algorithm succeed or fail on cert...