What are Extra Trees? The Extra Trees algorithm creates a large number of unpruned decision trees and makes predictions based on that. For a regression problem, the Extra Trees algorithm takes the average of all the predictions made by the decision trees. And for a...
A Support Vector Machine (SVM) uses a supervised learning method to solve regression or classification problems. Let’s say a dataset has n features. So, we can think of an n-dimensional space formed by the features. And a hyperplane is an (n-1) dimensional subspace...
The naive Bayes classifier is a probabilistic classifier based on the Bayes theorem. Let’s say we have a dataset with features X = [x1, x2, ..., xn]. And we need to determine the output label y based on these n features. Now, as per Bayes’ theorem: $latex...
Random forests use an ensemble learning method for classification or regression. A random forest classifier is used to solve classification problems. When we train a random forest with training data, it generates several decision trees. And then, when input features...
In our previous articles, we discussed how to solve regression problems using regression trees and classification problems using classification trees. We can also plot decision trees using the plot_tree() function from the sklearn.tree module. In this article, we will...
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