Quadratic Mutual Information Feature Selection
نویسندگان
چکیده
منابع مشابه
Quadratic Mutual Information Feature Selection
We propose a novel feature selection method based on quadratic mutual information which has its roots in Cauchy–Schwarz divergence and Renyi entropy. The method uses the direct estimation of quadratic mutual information from data samples using Gaussian kernel functions, and can detect second order non-linear relations. Its main advantages are: (i) unified analysis of discrete and continuous dat...
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Methods of feature evaluation are developed and discussed based on information theoretical learning (ITL). Mutual information was shown in the literature to be more robust and precise to evaluate a feature set. In this paper; we propose to use quadratic mutual information (QMI) for feature evaluation. The concept of information potential leads to a more clearly physical meaning of the evaluatio...
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Mutual Information (MI) is a powerful concept from information theory used in many application fields. For practical tasks it is often necessary to estimate the Mutual Information from available data. We compare state of the art methods for estimating MI from continuous data, focusing on the usefulness for the feature selection task. Our results suggest that many methods are practically relevan...
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Feature selection is used in many application areas relevant to expert and intelligent systems, such as data mining and machine learning, image processing, anomaly detection, bioinformatics and natural language processing. Feature selection based on information theory is a popular approach due its computational efficiency, scalability in terms of the dataset dimensionality, and independence fro...
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ژورنال
عنوان ژورنال: Entropy
سال: 2017
ISSN: 1099-4300
DOI: 10.3390/e19040157