Book My Show Interview Question | Low Bias & High Variance
Question
You came to know that your model is suffering from low bias and high variance. Which algorithm should you use to tackle it? Why?
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Machine Learning
55 years
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Answers ( 2 )
If our model is suffering from low bias and high variance then our model is suffering from overfitting. To prevent overfitting, we can use regularization L1 or L2. If we are using a neural network we can introduce dropout. We can also use early stopping to prevent overfitting.
Generally, you can try ensemble methods, for example RandomForest, XgBoost etc.
These techniques build several models and average the output of all the models
which leads to reduction in variance. While using these methods, you can try techniques
like cross validation, regularization which help in reducing the variance.