What is the importance of dimensionality reduction?

1.	What is the importance of dimensionality reduction?
Answer» The PROCESS of DIMENSIONALITY reduction CONSTITUTES reducing the number of features in a dataset to avoid overfitting and reduce the variance. There are mostly 4 advantages of this process: This reduces the storage space and time for model execution. Removes the ISSUE of multi-collinearity thereby improving the parameter interpretation of the ML model. Makes it easier for visualizing DATA when the dimensions are reduced. Avoids the curse of increased dimensionality.

Answer»

The PROCESS of DIMENSIONALITY reduction CONSTITUTES reducing the number of features in a dataset to avoid overfitting and reduce the variance. There are mostly 4 advantages of this process:

This reduces the storage space and time for model execution.
Removes the ISSUE of multi-collinearity thereby improving the parameter interpretation of the ML model.
Makes it easier for visualizing DATA when the dimensions are reduced.
Avoids the curse of increased dimensionality.

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What is the importance of dimensionality reduction?

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