Avoiding Data Overfitting In Machine Learning Models
Last Updated on November 9, 2023 by Editorial Team
Author(s): Don Kaluarachchi
Originally published on Towards AI.
Embrace robust model generalization instead
Image by Don Kaluarachchi (author)
In the world of machine learning, overfitting is a common issue causing models to struggle with new data.
Let us look at some practical tips to avoid this problem.
Before we dive into the solutions, let us understand overfitting.
Imagine teaching a kid to distinguish between cats and dogs.
Instead of grasping the essence of ‘whiskers’ and ‘fluffiness,’ the kid memorizes every fur pattern in your living room.
That is overfitting in a nutshell.
It is when your model becomes a parrot — repeating training data instead of understanding the concepts.
Why does this happen?
Blame it on the model being too complex.
It is… Read the full blog for free on Medium.
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