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Search results for javascript decision trees
decision-trees
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javascript
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14 search results found
Yggdrasil Decision Forests
⭐
403
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
Decision Tree Js
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237
Small JavaScript implementation of ID3 Decision tree
Silverdecisions
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93
Software for creating and analyzing decision trees.
Decision Tree Visualization Spark
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39
🌲 Decision Tree Visualization for Apache Spark
R2d3 Decision Tree
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33
A clone of the animated decision tree at http://www.r2d3.us/ in React, React-Motion, and d3
Ecpoint Calibrate
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20
Interactive GUI (developed in Python) for calibration and conditional verification of numerical weather prediction model outputs.
Mallard
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18
Data classification algorithms
Rfvis
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16
A tool for visualizing the structure and performance of Random Forests 🌳
Decision Tree Builder
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15
Build serialisable flowchart-style decision trees with D3.
Voice4rural
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12
A complete one stop solution for all the problems of Rural area people. 👩🏻🌾
Apps Flowchart
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11
Build a flowchart based on linked records.
Photonic
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11
Partition your React components based on props & state
Wink Regression Tree
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11
Decision Tree to predict the value of a continuous target variable
Automl Js
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9
Automated machine learning in JavaScript, in browser locally or in node.
Craft Ai Client Js
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9
craft ai API isomorphic javascript client
Decision Tree
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8
decision tree, random forests, based by d3, 决策树,随机森林,基于D3开发
Decision Tree
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8
A utility for traversing decision trees by selecting options
Ubcsimulator
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7
Decisiontree
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5
A web browser user interface element and algorithm for parsing and making decisions through a tree of nested inter-dependent questions & decisions. This version depends on jQuery but the dependency is easy to remove.
Decision
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5
A library for making decision trees.
Decisiontree
⭐
5
Implementation of Decision Tree Learning Method called ID3 Algorithm using Javascript in HTML5 Canvas.
Dss Plugin Decision Tree Builder
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5
Dataiku DSS plugin to manually build decision trees and use them to score and evaluate datasets
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