A Novel Meta Learning Framework for Feature Selection using Data Synthesis and Fuzzy Similarity

This paper presents a novel meta learning framework for feature selection (FS) based on fuzzy similarity. The proposed method aims to recommend the best FS method from four candidate FS methods for any given dataset. This is achieved by firstly constructing a large training data repository using dat...

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Hauptverfasser:	Shen, Zixiao, Chen, Xin, Garibaldi, Jonathan M
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning Statistics - Machine Learning
Online-Zugang:	Volltext bestellen
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