Data Preprocessing Techniques


Data preprocessing is a data mining technique that involves transforming raw data into an understandable format. It is a crucial step in the data analysis process as it helps to improve the quality of data, reduce errors, and increase the accuracy of the results. Data preprocessing techniques include data cleaning, data integration, data transformation, and data reduction. Data cleaning involves removing or correcting any errors or inconsistencies in the data. Data integration involves combining data from multiple sources into a single dataset. Data transformation involves converting data into a suitable format for analysis. Data reduction involves reducing the size of the dataset while preserving its integrity and usefulness.


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