Feature selection and replacement by clustering attributes
نویسندگان
چکیده
منابع مشابه
Feature Selection with Attributes Clustering by Maximal Information Coefficient
Feature selection is usually a separate procedure which can not benefit from result of the data exploration. In this paper, we propose a unsupervised feature selection method which could reuse a specific data exploration result. Furthermore, our algorithm follows the idea of clustering attributes and combines two state-of-the-art data analyzing methods, that’s maximal information coefficient an...
متن کاملAn Effective Attribute Clustering Approach for Feature Selection and Replacement
Feature selection is an important pre-processing step in mining and learning. A good set of features can not only improve the accuracy of classification, but also reduce the time to derive rules. It is executed especially when the amount of attributes in a given training data is very large. In this paper, an attribute clustering method based on genetic algorithms is proposed for feature selecti...
متن کاملFeature selection using nearest attributes
—Feature selection is an important problem in high-dimensional data analysis and classification. Conventional feature selection approaches focus on detecting the features based on a redundancy criterion using learning and feature searching schemes. In contrast, we present an approach that identifies the need to select features based on their discriminatory ability among classes. Area of overlap...
متن کاملOptimal Feature Selection for Data Classification and Clustering: Techniques and Guidelines
In this paper, principles and existing feature selection methods for classifying and clustering data be introduced. To that end, categorizing frameworks for finding selected subsets, namely, search-based and non-search based procedures as well as evaluation criteria and data mining tasks are discussed. In the following, a platform is developed as an intermediate step toward developing an intell...
متن کاملFeature Selection and Document Clustering
Feature selection is a basic step in the construction of a vector space or bag of words model [BB99]. In particular, when the processing task is to partition a given document collection into clusters of similar documents a choice of good features along with good clustering algorithms is of paramount importance. This chapter suggests two techniques for feature or term selection along with a numb...
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: Vietnam Journal of Computer Science
سال: 2013
ISSN: 2196-8888,2196-8896
DOI: 10.1007/s40595-013-0004-3