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Why is Data Preprocessing required? Explain the different steps involved in Data Preprocessing
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Data Preprocessing is required because:

  • Real world data are generally:

    Incomplete: Missing attribute values, missing certain attributes of importance, or having only aggregate data

    Noisy: Containing errors or outliers

    Inconsistent: Containing discrepancies in codes or names

  • Steps in Data preprocessing:

    1. Data cleaning:

    • Data cleaning, also called data cleansing or …

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