Lasso, Ridge Regression Algorithm | Machine Learning
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Lasso, Ridge Regression Algorithm
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- 21/06/2022
In this video, we have covered what is Lasso & ridge regression & what are the problems that one can encounter when using these techniques to train the models.
Lasso and ridge regression is a regularization technique, and it comes to training models. There are two problems one can encounter - Overfitting & Underfitting.
Let us see in detail what is overfitting & underfitting.
1) Overfitting - A statistical model or a machine learning algorithm is said to have under-fitting when it cannot capture the underlying trend of the data. 2) Underfitting - A statistical model is said to be over-fitted when we train it with a lot of data (just like fitting ourselves in oversized pants!). When a model gets trained with so much data, it starts learning from the noise and inaccurate data entries in our data set.
Ridge Regression - Ridge regression is a classification algorithm that works in part as it doesn’t require unbiased estimators.
Lasso Regression - Lasso regression is a regularization technique. It is used over regression methods for a more accurate prediction
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