Tag Archives: feature selection

Overfitting and Underfitting models in Machine Learning

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In most of our posts about machine learning, we’ve talked about overfitting and underfitting. But most of us don’t yet know what those two terms mean. What does it acutally mean when a model is overfit, or underfit? Why are they considered not good? Read more...

Different types of Validations in Machine Learning (Cross Validation)

cross_validation

Now that we know what is feature selection and how to do it, let’s move our focus to validating the efficiency of our model. This is known as validation or cross validation, depending on what kind of validation method you’re using. Read more...

Different methods of feature selection

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In our previous post, we discussed what is feature selection and why we need feature selection. In this post, we’re going to look at the different methods used in feature selection. There are three main classification of feature selection methods – Filter Methods, Wrapper Methods, and Embedded Methods. Read more...