Search Results for "decision tree"
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Showing 53 open source projects for "decision tree"
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dtreeviz
Python library for decision tree visualization & model interpretation
A python library for decision tree visualization and model interpretation. Decision trees are the fundamental building block of gradient boosting machines and Random Forests(tm), probably the two most popular machine learning models for structured data. Visualizing decision trees is a tremendous aid when learning how these models work and when interpreting models. -
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BehaviorTree.CPP
C++ behavior tree library for robotics and AI decision systems
BehaviorTree.CPP is a C++ library designed to create, manage, and execute behavior trees, a widely used model for decision-making in robotics and artificial intelligence systems. It provides a flexible and modular framework that allows developers to define complex behaviors as reusable tree structures composed of nodes. BehaviorTree.CPP emphasizes performance and real-time execution, making it particularly suitable for robotics applications where responsiveness is critical. ... -
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LightGBM
Gradient boosting framework based on decision tree algorithms
LightGBM or Light Gradient Boosting Machine is a high-performance, open source gradient boosting framework based on decision tree algorithms. Compared to other boosting frameworks, LightGBM offers several advantages in terms of speed, efficiency and accuracy. Parallel experiments have shown that LightGBM can attain linear speed-up through multiple machines for training in specific settings, all while consuming less memory. LightGBM supports parallel and GPU learning, and can handle large-scale data. ... -
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FLEXible
Federated Learning (FL) experiment simulation in Python
FLEXible (Federated Learning Experiments) is a Python framework offering tools to simulate FL with deep learning. It includes built-in datasets (MNIST, CIFAR10, Shakespeare), supports TensorFlow/PyTorch, and has extensions for adversarial attacks, anomaly detection, and decision trees. -
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Beehave
Behavior tree AI for Godot Engine
Beehave is a powerful AI behavior tree framework designed as an addon for the Godot game engine, enabling developers to create sophisticated and dynamic non-player character behaviors in games. It uses a node-based system that integrates directly into the Godot scene tree, allowing developers to visually design and organize complex AI logic in a structured and intuitive way. -
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The AI Scientist-v2
Workshop-Level Automated Scientific Discovery via Agentic Tree Search
...It introduces a generalized framework that removes reliance on predefined templates, enabling broader applicability across multiple machine learning domains and more open-ended exploration of research problems. A key innovation is its progressive agentic tree search, which systematically explores experimental paths and is coordinated by an experiment manager agent that guides decision-making. The system also integrates automated review mechanisms, including vision-language feedback loops, to iteratively refine the quality of generated research outputs. -
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GeoDMA
Geographic feature extraction and data mining
GeoDMA is a plugin for TerraView software, used for geographical data mining. With a single image, the user can perform segmentation, attributes extraction, normalization and classification. -
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treeminder
a free mind mapping tool, to especially assist decision making
I've been trying to develop an idea of a project, but the wide range of possibilities with all their outcomes, cons and pros and whatnot got my mind overloaded. There was no way I could keep or process that much information with my bare mind. So, I've checked the mind mapping tools available in the market, both free and commercial ones, yet they were either clunky or overkilling for my needs. Thus, I've made my own thing, and decided to share it with everyone who might find it useful for... -
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DecisionTree.jl
Julia implementation of Decision Tree (CART) Random Forest algorithm
Julia implementation of Decision Tree (CART) and Random Forest algorithms. -
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Repo of Tree of Thoughts (ToT)
Implementation of "Tree of Thoughts
Language models are increasingly being deployed for general problem-solving across a wide range of tasks, but are still confined to token-level, left-to-right decision-making processes during inference. This means they can fall short in tasks that require exploration, strategic lookahead, or where initial decisions play a pivotal role. To surmount these challenges, we introduce a new framework for language model inference, Tree of Thoughts (ToT), which generalizes over the popular Chain of Thought approach to prompting language models and enables exploration over coherent units of text (thoughts) that serve as intermediate steps toward problem-solving. ... -
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MuZero General
A commented and documented implementation of MuZero
muzero-general is an open-source implementation of the MuZero reinforcement learning algorithm introduced by DeepMind. MuZero is a model-based reinforcement learning method that combines neural networks with Monte Carlo Tree Search to learn decision-making policies without requiring explicit knowledge of the environment’s dynamics. The repository provides a well-documented and commented implementation designed primarily for educational purposes. It allows researchers and developers to train reinforcement learning agents that can learn to play games such as Atari environments or board games. ... -
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ModelFox
ModelFox makes it easy to train, deploy, and monitor ML models
...Train a machine learning model by running modelfox train with the path to a CSV file and the name of the column you want to predict. The CLI automatically transforms your data into features, trains a number of linear and gradient boosted decision tree models to predict the target column, and writes the best model to a .modelfox file. If you want more control, you can provide a config file. -
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Awesome Decision Tree Papers
A collection of research papers on decision, classification, etc.
A collection of research papers on decision, classification and regression trees with implementations. -
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Toxtree: Toxic Hazard Estimation
Toxicity prediction for chemical compounds
...The latest version includes the following toxicity prediction modules: -Cramer rules (oral toxicity) -Toxicity mode of action via Verhaar scheme -Skin irritation and Eye irritation prediction -Benigni / Bossa rulebase for mutagenicity and carcinogenicity prediction -START biodegradation and persistence prediction -Skin sensitisation reactivity domain -Kroes TTC Decision tree -SMARTCyp - Cytochrome P450-Mediated Drug Metabolism and metabolites prediction -Structure Alerts for the in vivo micronucleus assay in rodents (ISSMIC) -Structural Alerts for Functional Group Identification (ISSFUNC) -Structural alerts associated with covalent protein binding and DNA binding. - Ames mutagenicity Toxtree provides a plugin framework to incorporate different approaches to the estimation. ... -
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Machine-Learning
kNN, decision tree, Bayesian, logistic regression, SVM
Machine-Learning is a repository focused on practical machine learning implementations in Python, covering classic algorithms like k-Nearest Neighbors, decision trees, naive Bayes, logistic regression, support vector machines, linear and tree-based regressions, and likely corresponding code examples and documentation. It targets learners or practitioners who want to understand and implement ML algorithms from scratch or via standard libraries, gaining hands-on experience rather than relying solely on black-box frameworks. ... -
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ASCII Art
Real-Time ASCII Art Rendering Library
A header-only, C/C++ library that lets you transform an input image or video frame into printable ASCII characters in real-time using a single decision tree. ASCII Art is a single header, C/C++ library developed by PixLab and based on the work of Nenad Markus that let you transform an input image or video frame into printable ASCII characters at real-time using a single decision tree. Real-time performance is achieved by using pixel intensity comparison inside the internal nodes of the tree. -
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Varied Tree Weka Package
Random Tree-based classifier featuring multiple node tests.
Weka package extension with custom decision tree classifier (based on Random Tree) generating three different tests in its nodes: traditional value test (e.g. x1 < 3.4), relational test (e.g. x1 < x2) and weighted relational test (e.g. x1 < 0.78 * x2). Decision on node level is made based on weighted vote made by each test. -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than... -
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CCZero (中国象棋Zero)
Implement AlphaZero/AlphaGo Zero methods on Chinese chess
ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics. -
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CodelPlant
Codelplant stat. multi-regression M-learning for leaves segmentation
CodelPlant is based on the creation of a statistical multi-regression decision tree from data obtained by pixel RGB-HSB machine learning analysis. The model is training with human observation, so the human factor is being entered the process. -
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Simple Value Tree is an Excel Add-in for Multiple-Criteria Decision Analysis (MCDA). This Add-in was created by Huong Lien Le and Gilberto Montibeller in 2017, and further developed by Hangchen Zhu in 2018.
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MYRA
A collection of ACO algorithms for the data mining classification task
MYRA is a collection of Ant Colony Optimization (ACO) algorithms for the data mining classification task. It includes popular rule induction and decision tree induction algorithms. The algorithms are ready to be used from the command line or can be easily called from your own Java code. They are build using a modular architecture, so they can be easily extended to incorporate different procedures and/or use different parameter values. This project is now hosted at: https://github.com/febo/myra -
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faif
C++ header only library with AI and bioinformatics algorithms
C++ header only library, small and fast; Naive Bayesian Classifier, Decision Tree Classifier (ID3), DNA/RNA nucleotide second structure predictor, timeseries management, timeseries prediction, generic Evolutionary Algorithm, generic Hill Climbing algorithm and others. -
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Choose Your Own Adventure Writer
Choose Your Own Adventure style authoring and reading
A simple and efficient tool for handling the complicated task of writing a non-linear narrative (choose your own adventure style) story. Features an interface for reading stories written with the software. Writing / Authoring component features intuitive workspace, and 'decision tree' views for navigating back and forward through branching narratives. -
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The PCI toolkit is based on a decision tree assessment methodology, which helps you identify if your web applications are part of the PCI-DSS scope and how to apply the PCI-DSS requirements. By decomposing , one by one , you will be able to create an assessment and a final report of your scope delimitation and which OWASP guidelines must be used
