Explanation:
Binning is a technique used to convert numeric (continuous) data into categorical data by dividing the data into discrete intervals or bins. This process helps in simplifying the data analysis and can improve the performance of machine learning models by reducing noise or non-linearity.
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What is the main goal of binning in the context of machine learning?
A
To enhance the granularity of numeric data.
B
To transform numeric data into categorical data by organizing it into specific bins or ranges.
C
To decrease the dataset's size.
D
To change categorical data into numeric data.
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