What is Underfitting and how to solve it?

Underfitting is that the opposite of overfitting, and you will encounter this when the model is extremely simple to find out. For example, using the example of quality of life, real life is more complex than your model, so the predictions won’t yield the same, even in the training examples.

To fix this problem of underfitting:

  • Select the most powerful model, which has many parameters.
  • Feed the best features into your algorithm. Here, I’m referring to feature engineering.
  • Reduce the constraints on your model.

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