Why Feature Engineering is important? The features in your data will directly influence the accuracy of your model. The better features gives good accuracy on your test data.
Why Feature Engineering is important?
The features in your data will directly influence the accuracy of your model. The better features gives good accuracy on your test data. The better the features that you choose, the better the results you will achieve.
The General view is adding more features increases the model/classifier’s performance.
Let us see why this is not the case:
Choosing more number of features will usually degrade classifier’s performance.
CURSE OF DIMENSIONALITY
Having n initial features, it is possible to select (2^n ) combinations of features(2^n subsets are possible).
We just can’t go over all the possible (2^n) subsets.
Feature Selection is an optimization problem
Evaluating the Feature Subset
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