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Ankita paunikar's Blog (1)

Intuition behind Bias-Variance trade-off, Lasso and Ridge Regression

Linear regression uses Ordinary Least square method to find the best coefficient estimates. One of the assumptions of Linear regression is that the variables are not correlated with each other. However, when the multicollinearity exists in the dataset (two or more variables are highly correlated with each other) Ordinary Least square method cannot be that effective. In this blog, we will talk about two methods which are slightly better than Ordinary Least Square method – Lasso and Ridge…

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Added by ankita paunikar on January 4, 2018 at 9:30am — No Comments

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