67 Repositories
Python bagging-ensemble Libraries
Data stream analytics: Implement online learning methods to address concept drift in data streams using the River library. Code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streams" accepted in IEEE GlobeCom 2021.
PWPAE-Concept-Drift-Detection-and-Adaptation This is the code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT
SentimentArcs: a large ensemble of dozens of sentiment analysis models to analyze emotion in text over time
SentimentArcs - Emotion in Text An end-to-end pipeline based on Jupyter notebooks to detect, extract, process and anlayze emotion over time in text. E
Code for intrusion detection system (IDS) development using CNN models and transfer learning
Intrusion-Detection-System-Using-CNN-and-Transfer-Learning This is the code for the paper entitled "A Transfer Learning and Optimized CNN Based Intrus
Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning
Ensemble Knowledge Guided Sub-network Search and Fine-tuning for Filter Pruning This repository is official Tensorflow implementation of paper: Ensemb
Over-the-Air Ensemble Inference with Model Privacy
Over-the-Air Ensemble Inference with Model Privacy This repository contains simulations for our private ensemble inference method. Installation Instal
One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking
One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking This is an official implementation for NEAS presented in CVPR
Computational inteligence project on faces in the wild dataset
Table of Contents The general idea How these scripts work? Loading data Needed modules and global variables Parsing the arrays in dataset Extracting a
Ensemble Visual-Inertial Odometry (EnVIO)
Ensemble Visual-Inertial Odometry (EnVIO) Authors : Jae Hyung Jung, Yeongkwon Choe, and Chan Gook Park 1. Overview This is a ROS package of Ensemble V
EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients.
EASY - Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients. This repository is the official im
Ensemble Learning Priors Driven Deep Unfolding for Scalable Snapshot Compressive Imaging [PyTorch]
Ensemble Learning Priors Driven Deep Unfolding for Scalable Snapshot Compressive Imaging [PyTorch] Abstract Snapshot compressive imaging (SCI) can rec
Novel and high-performance medical image classification pipelines are heavily utilizing ensemble learning strategies
An Analysis on Ensemble Learning optimized Medical Image Classification with Deep Convolutional Neural Networks Novel and high-performance medical ima
Voice Gender Recognition
In this project it was used some different Machine Learning models to identify the gender of a voice (Female or Male) based on some specific speech and voice attributes.
Open solution to the Toxic Comment Classification Challenge
Starter code: Kaggle Toxic Comment Classification Challenge More competitions 🎇 Check collection of public projects 🎁 , where you can find multiple
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering This repository provides the source code of "Consensus Learning
Deep Ensemble Learning with Jet-Like architecture
Ransomware analysis using DEL with jet-like architecture comprising two CNN wings, a sparse AE tail, a non-linear PCA to produce a diverse feature space, and an MLP nose
The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis.
deep-learning-LAM-avulsion-diagnosis The code succinctly shows how our ensemble learning based on deep learning CNN is used for LAM-avulsion-diagnosis
General Assembly's 2015 Data Science course in Washington, DC
DAT8 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (8/18/15 - 10/29/15). Instructor: Kevin Markham (
Parameter-ensemble-differential-evolution - Shows how to do parameter ensembling using differential evolution.
Ensembling parameters with differential evolution This repository shows how to ensemble parameters of two trained neural networks using differential e
AutoGluon: AutoML for Text, Image, and Tabular Data
AutoML for Text, Image, and Tabular Data AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in yo
Class-imbalanced / Long-tailed ensemble learning in Python. Modular, flexible, and extensible
IMBENS: Class-imbalanced Ensemble Learning in Python Language: English | Chinese/中文 Links: Documentation | Gallery | PyPI | Changelog | Source | Downl
Official PyTorch implementation of "Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble" (NeurIPS'21)
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble This is the code for reproducing the results of the paper Uncertainty-Bas
Implemented four supervised learning Machine Learning algorithms
Implemented four supervised learning Machine Learning algorithms from an algorithmic family called Classification and Regression Trees (CARTs), details see README_Report.
Pytorch implementation of SenFormer: Efficient Self-Ensemble Framework for Semantic Segmentation
SenFormer: Efficient Self-Ensemble Framework for Semantic Segmentation Efficient Self-Ensemble Framework for Semantic Segmentation by Walid Bousselham
A full pipeline AutoML tool for tabular data
HyperGBM Doc | 中文 We Are Hiring! Dear folks,we are offering challenging opportunities located in Beijing for both professionals and students who are k
Learning with Subset Stacking
Learning with Subset Stacking (LESS) LESS is a new supervised learning algorithm that is based on training many local estimators on subsets of a given
Hypernetwork-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels
Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels The implementation of Hypernet-Ensemble Le
The best solution of the Weather Prediction track in the Yandex Shifts challenge
yandex-shifts-weather The repository contains information about my solution for the Weather Prediction track in the Yandex Shifts challenge https://re
Official repository for: Continuous Control With Ensemble DeepDeterministic Policy Gradients
Continuous Control With Ensemble Deep Deterministic Policy Gradients This repository is the official implementation of Continuous Control With Ensembl
Official implementation of Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models at NeurIPS 2021
Representer Point Selection via Local Jacobian Expansion for Classifier Explanation of Deep Neural Networks and Ensemble Models This repository is the
Set of methods to ensemble boxes from different object detection models, including implementation of "Weighted boxes fusion (WBF)" method.
Set of methods to ensemble boxes from different object detection models, including implementation of "Weighted boxes fusion (WBF)" method.
DuBE: Duple-balanced Ensemble Learning from Skewed Data
DuBE: Duple-balanced Ensemble Learning from Skewed Data "Towards Inter-class and Intra-class Imbalance in Class-imbalanced Learning" (IEEE ICDE 2022 S
IMBENS: class-imbalanced ensemble learning in Python.
IMBENS: class-imbalanced ensemble learning in Python. Links: [Documentation] [Gallery] [PyPI] [Changelog] [Source] [Download] [知乎/Zhihu] [中文README] [a
Deep Learning with PyTorch made easy 🚀 !
Deep Learning with PyTorch made easy 🚀 ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c
MinHash, LSH, LSH Forest, Weighted MinHash, HyperLogLog, HyperLogLog++, LSH Ensemble
datasketch: Big Data Looks Small datasketch gives you probabilistic data structures that can process and search very large amount of data super fast,
zeus is a Python implementation of the Ensemble Slice Sampling method.
zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl
A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines
A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines Understanding the results of deep neural networks is
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention
AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil
An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)
An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)
Replication Package for "An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Datasets"
Replication Package for "An Empirical Study of the Effectiveness of an Ensemble of Stand-alone Sentiment Detection Tools for Software Engineering Data
AI-UPV at IberLEF-2021 EXIST task: Sexism Prediction in Spanish and English Tweets Using Monolingual and Multilingual BERT and Ensemble Models
AI-UPV at IberLEF-2021 EXIST task: Sexism Prediction in Spanish and English Tweets Using Monolingual and Multilingual BERT and Ensemble Models Descrip
Code for Greedy Gradient Ensemble for Visual Question Answering (ICCV 2021, Oral)
Greedy Gradient Ensemble for De-biased VQA Code release for "Greedy Gradient Ensemble for Robust Visual Question Answering" (ICCV 2021, Oral). GGE can
Implementation of Bagging and AdaBoost Algorithm
Bagging-and-AdaBoost Implementation of Bagging and AdaBoost Algorithm Dataset Red Wine Quality Data Sets For simplicity, we will have 2 classes of win
Intrusion Detection System using ensemble learning (machine learning)
IDS-ML implementation of an intrusion detection system using ensemble machine learning methods Data set This project is carried out using the UNSW-15
Merlion: A Machine Learning Framework for Time Series Intelligence
Merlion: A Machine Learning Library for Time Series Table of Contents Introduction Installation Documentation Getting Started Anomaly Detection Foreca
Merlion: A Machine Learning Framework for Time Series Intelligence
Merlion is a Python library for time series intelligence. It provides an end-to-end machine learning framework that includes loading and transforming data, building and training models, post-processing model outputs, and evaluating model performance. I
2021海华AI挑战赛·中文阅读理解·技术组·第三名
文字是人类用以记录和表达的最基本工具,也是信息传播的重要媒介。透过文字与符号,我们可以追寻人类文明的起源,可以传播知识与经验,读懂文字是认识与了解的第一步。对于人工智能而言,它的核心问题之一就是认知,而认知的核心则是语义理解。
Neural Ensemble Search for Performant and Calibrated Predictions
Neural Ensemble Search Introduction This repo contains the code accompanying the paper: Neural Ensemble Search for Performant and Calibrated Predictio
This repo is customed for VisDrone.
Object Detection for VisDrone(无人机航拍图像目标检测) My environment 1、Windows10 (Linux available) 2、tensorflow = 1.12.0 3、python3.6 (anaconda) 4、cv2 5、ensemble
This repo is customed for VisDrone.
Object Detection for VisDrone(无人机航拍图像目标检测) My environment 1、Windows10 (Linux available) 2、tensorflow = 1.12.0 3、python3.6 (anaconda) 4、cv2 5、ensemble
Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning
The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I
Scikit-learn compatible estimation of general graphical models
skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships
A Python library for dynamic classifier and ensemble selection
DESlib DESlib is an easy-to-use ensemble learning library focused on the implementation of the state-of-the-art techniques for dynamic classifier and
(AAAI' 20) A Python Toolbox for Machine Learning Model Combination
combo: A Python Toolbox for Machine Learning Model Combination Deployment & Documentation & Stats Build Status & Coverage & Maintainability & License
The Python ensemble sampling toolkit for affine-invariant MCMC
emcee The Python ensemble sampling toolkit for affine-invariant MCMC emcee is a stable, well tested Python implementation of the affine-invariant ense
Scikit-learn compatible estimation of general graphical models
skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.
Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The
Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.
Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r
Python package for stacking (machine learning technique)
vecstack Python package for stacking (stacked generalization) featuring lightweight functional API and fully compatible scikit-learn API Convenient wa
Stacked Generalization (Ensemble Learning)
Stacking (stacked generalization) Overview ikki407/stacking - Simple and useful stacking library, written in Python. User can use models of scikit-lea
The Python ensemble sampling toolkit for affine-invariant MCMC
emcee The Python ensemble sampling toolkit for affine-invariant MCMC emcee is a stable, well tested Python implementation of the affine-invariant ense
Automates Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning :rocket:
MLJAR Automated Machine Learning Documentation: https://supervised.mljar.com/ Source Code: https://github.com/mljar/mljar-supervised Table of Contents
ML-Ensemble – high performance ensemble learning
A Python library for high performance ensemble learning ML-Ensemble combines a Scikit-learn high-level API with a low-level computational graph framew
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.
Xcessiv Xcessiv is a tool to help you create the biggest, craziest, and most excessive stacked ensembles you can think of. Stacked ensembles are simpl
Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.
Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r
A data-driven approach to quantify the value of classifiers in a machine learning ensemble.
Documentation | External Resources | Research Paper Shapley is a Python library for evaluating binary classifiers in a machine learning ensemble. The
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
H2O H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Fl