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Decision Tree Pruning: The Hows and Whys

KDnuggets

Decision trees are a machine learning algorithm that is susceptible to overfitting. One of the techniques you can use to reduce overfitting in decision trees is pruning.

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Simplifying Decision Tree Interpretability with Python & Scikit-learn

KDnuggets

This post will look at a few different ways of attempting to simplify decision tree representation and, ultimately, interpretability. All code is in Python, with Scikit-learn being used for the decision tree modeling.

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Understanding by Implementing: Decision Tree

KDnuggets

Learn how a Decision Tree works and implement it in Python.

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A Complete Guide To Decision Tree Software

KDnuggets

Decision tree models are used to classify information into meaningful sequential results. Find out everything else you need to know here.

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Decision Tree Algorithm, Explained

KDnuggets

All you need to know about decision trees and how to build and optimize decision tree classifier.

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Trinary Decision Trees for missing value handling

Hacker News

This paper introduces the Trinary decision tree, an algorithm designed to improve the handling of missing data in decision tree regressors and classifiers. Unlike other approaches, the Trinary decision tree does not assume that missing values contain any information about the response.

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Understanding Decision Trees for Classification in Python

KDnuggets

This tutorial covers decision trees for classification also known as classification trees, including the anatomy of classification trees, how classification trees make predictions, using scikit-learn to make classification trees, and hyperparameter tuning.