A Data Mining Objective Function with Feature Selection Algorithm Using Document Clustering

Provided by: International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE)
Topic: Data Management
Format: PDF
Conventional feature selection classifiers work with known and precise data values. In recent data collection methods, appreciable amount of attributes are uncertain. The uncertain attributes, in almost all applications, have more influences on the dataset on information classification and feature selection constructs. Uncertainty needs to be handled properly reasons for uncertainty are due to measurement errors, quantization errors, data staleness and multiple repeated measurements. Uncertainty of a document item is represented in terms of multiple values.

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