Bayesian Decision Trees ... a pruning step. This algorithm generates the greedy-modal tree (GMT) which is applicable to both regression and classification problems. We tested the algorithm on various ...

Abstract: Decision tree algorithms are very popular in the field of data mining. This paper proposes a distributed decision tree algorithm and shows examples of its implementation on big data ...

Decision Tree is the simple but powerful classification algorithm of machine learning where a tree or graph-like structure is constructed to display algorithms and reach possible consequences of a ...

The name “decision tree” comes from the fact that the algorithm keeps dividing the dataset down into smaller and smaller portions until the data has been divided into single instances, which are then ...

Abstract: With the advent of the computer science, the data volume that needed to be processed under ... Bearing this in mind, we made an intensive study on the optimization of decision tree algorithm ...

This repository contains code and documentation for a project that demonstrates the classification of the Iris dataset using the Decision Tree Classifier algorithm. The Decision Tree is a popular and ...

Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover ...

Data Science Algorithms in a Week addresses all problems related to ... This book covers algorithms such as k-nearest neighbors, Naive Bayes, decision trees, random forest, k-means, regression, and ...