@harimindi wrote:
While working on building models from large datasets, feature engineering is a must. I understand this can be creation of new feature or removal of some existing features. I am focussing on the removal of features and would like to know what parameters need to be considered when removing some features. For example, i am currently looking at variables that have more than 50 - 60 % same values as i think these might not contribute to the model. Are there are any other things that we need to consider when removing variables and overall is it a good practice to remove features.
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