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3.2. Data Preprocessing Since the total number of datasets was large, they could have contained features or outliers that would not have been helpful for training. If there was no proper preprocessing, the trained model would not have been able to identify various intrusion attacks. To this end, this study was focused on data preprocessing, including data merging, data cleaning, data transformation and split, and numerical standardization.
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