Data Attribute Reduction using Binary Conversion

Provided by: WSEAS
Topic: Data Management
Format: PDF
While learning with data having large number of attribute, a system is easy to freeze or shut down or run for a long time. Therefore, the proposed Binary Conversion (BC) is a novel method to solve this kind of large attribute problem in machine learning. The purpose of BC is to reduce data dimensions by a binary conversion process. All the attributes are reserved but combined into few numbers of new attributes instead of that some attributes are removed.

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