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DecisionTree.jl

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DecisionTree.jl Reviews

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Bishnu M.
BM
Bishnu M.
03/20/2023
Validated Reviewer
Review source: G2 invite
Incentivized Review

DecisionTree.jl helps to implement Classification and Regression Tree in few simple steps

DecicionTree.jl is a CART (Classification and Regression Tree) package in the Julia machine learning programing language. Various steps like loading data, segregating data into training and testing, and building a model is very easy to implement using this package in Julia. There is no need to transpose data as DecisionTree.jl does not require it. It just takes a two lines statement to build the model providing a few arguments (e.g. depth, minimum number of samples in leaf, minimum number of samples in split etc.) as per user requirement. This package saves lots of time and money for regression and classification problems compared to creating a decision tree ML model from scratch. We used decisionTree.jl for a retail client to build a model to classify potential customer data and were able to achieve near about 70% accuracy, which is considered as very good accuracy.
Saurabh B.
SB
Saurabh B.
IT Infrastructure & Cloud architect
03/14/2023
Validated Reviewer
Review source: G2 invite
Incentivized Review

Review for decision tree

Attended one of the session for Julia AI and decision tree.jl and found that to be insightful and useful. Its ability to convert the convert the problem in a working model was awesome
Manoj P.
MP
Manoj P.
Lead Consultant Infosys
03/09/2023
Validated Reviewer
Review source: G2 invite
Incentivized Review

Powerful package for building and using decision tress

Its support for Classification and regression tests, powered by high-performing language Julia

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What is DecisionTree.jl?

DecisionTree.jlDecisionTree.jl is an open-source Julia package for creating decision tree classifiers and regressors. It is designed to be highly efficient and flexible, offering users the ability to perform various machine learning tasks such as classification, regression, and even pruning of decision trees. This Julia library provides several algorithms, including CART (Classification and Regression Trees), ID3 (Iterative Dichotomiser 3), and Random Forests, facilitating robust data modeling and prediction tasks.The package is tailored for those familiar with the Julia programming language, leveraging Julia’s strengths in speed and mathematical computation to ensure high-performance implementation of decision tree algorithms. It is particularly suited for researchers, data scientists, and developers looking for a fast and reliable tool to incorporate into their data analysis workflows.

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