Variable Selection Based on Mutual Information
نویسندگان
چکیده
منابع مشابه
Feature Selection Based on Joint Mutual Information
A feature/input selection method is proposed based on joint mutual information. The new method is better than the existing methods based on mutual information in eliminating redundancy in the inputs. It is applied in a real world application to nd 2-D viewing coordinates for data visualization and to select inputs for a neural network classiier. The result shows that the new method can nd many ...
متن کاملOn Classification of Bivariate Distributions Based on Mutual Information
Among all measures of independence between random variables, mutual information is the only one that is based on information theory. Mutual information takes into account of all kinds of dependencies between variables, i.e., both the linear and non-linear dependencies. In this paper we have classified some well-known bivariate distributions into two classes of distributions based on their mutua...
متن کاملConditional Dynamic Mutual Information-Based Feature Selection
With emergence of new techniques, data in many fields are getting larger and larger, especially in dimensionality aspect. The high dimensionality of data may pose great challenges to traditional learning algorithms. In fact, many of features in large volume of data are redundant and noisy. Their presence not only degrades the performance of learning algorithms, but also confuses end-users in th...
متن کاملA Powerful Feature Selection approach based on Mutual Information
Feature selection aims to reduce the dimensionality of patterns for classificatory analysis by selecting the most informative instead of irrelevant and/or redundant features. In this paper we propose a novel feature selection measure based on mutual information and takes into consideration the interaction between features. The proposed measure is used to determine relevant features from the ori...
متن کاملInput Feature Selection by Mutual Information Based on Parzen Window
Mutual information is a good indicator of relevance between variables, and have been used as a measure in several feature selection algorithms. However, calculating the mutual information is difficult, and the performance of a feature selection algorithm depends on the accuracy of the mutual information. In this paper, we propose a new method of calculating mutual information between input and ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Communications for Statistical Applications and Methods
سال: 2009
ISSN: 2287-7843
DOI: 10.5351/ckss.2009.16.1.143