Data mining and machine learning techniques help us to better and deeper understanding of collected data. Meta-learning techniques extend this concept by providing methods for knowledge discovery process automatization. Meta-learning introduces various interesting concepts, including data meta-features, meta-knowledge, algorithm recommendation systems, autonomous process builders, etc. All these techniques aim to improve usually expensive and demanding data mining analysis. This paper focus on general overview of basic data mining, machine learning and meta-learning techniques, while focusing on state-of-the-art, basic formalisms and principles, interesting applications and possible future development in the field of meta-learning.
Keywords
Data Mining, DMA, KDD, Machine Learning, Meta-Learning
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