Feature Selection and Removing in Machine Learning
Last Updated on July 26, 2023 by Editorial Team
Author(s): Amit Chauhan
Originally published on Towards AI.
Improving model and its accuracy for high dimension data
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As we know the importance of features in the machine learning algorithms are playing a very crucial role in prediction analysis in any field.
When the data features become very complex then there are very high chances to get a multi-collinearity situation or high correlation between two and more features. This situation strikes badly on the training of data and it might go over-fitting or under-fitting of the data.
There are some methods to select and remove features as shown below:
Feature Selection Methods1. Uni-variate Selection2. Selecting… Read the full blog for free on Medium.
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