Apply Pre-Processing techniques to the training data set of Exam

Question

Apply Pre-Processing techniques to the training data set of Exam_Results Table.

07 Mar 2024

Answer :

Word Count : 358

To preprocess the training data set of the Exam_Results table, you can follow these steps:

1. Handling Missing Values: Identify and handle any missing values in the data set. You can either remove the rows with missing values or impute them using techniques like mean/median imputation, or more advanced methods like multiple imputation.

2. Encoding Categorical Variables: If your data set contains categorical variables, you need to encode them into numerical form for most machine learning algorithms. Common encoding techniques include one-hot encoding, label encoding, or target encoding.

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