An Optimum Model for the Retrieval of Missing Values for Data Cleansing Using Regression Analysis

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Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
An important aspect of the data mining is the pre-processing of the data. Pre-processing of the data is important because real world data is susceptible to inconsistencies, noise and missing values. Such a data cannot be used in data mining as that would produce highly inadequate results. There are basically two methods through which the authors can remove the problem of the missing values the first one is to ignore the data set with the missing value the second one is to predict those values. Prediction can be made based on assuming the continuity of the data or giving them some suitable value based on previous knowledge.
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