APPLICATION OF SUPERVISED LEARNING
CLASSIFICATION IN MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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How do you handle missing or corrupted data in a dataset?
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Drop missing rows or columns
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imputation can be done
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Assign a unique category to missing values
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All of the above
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Explanation:
Detailed explanation-1: -Deleting Rows with missing values. Impute missing values for continuous variable. Impute missing values for categorical variable. Other Imputation Methods. Using Algorithms that support missing values. Prediction of missing values. More items
Detailed explanation-2: -Mean, Median and Mode This is one of the most common methods of imputing values when dealing with missing data. In cases where there are a small number of missing observations, data scientists can calculate the mean or median of the existing observations open in new.
Detailed explanation-3: -So, Assigning a unique category is not any of the techniques used in handling missing or corrupted values.
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