297 Repositories
Python clustering-evaluation Libraries
Open-Source CI/CD platform for ML teams. Deliver ML products, better & faster. ⚡️🧑🔧
Deliver ML products, better & faster Giskard is an Open-Source CI/CD platform for ML teams. Inspect ML models visually from your Python notebook 📗 Re
KwaiRec: A Fully-observed Dataset for Recommender Systems (Density: Almost 100%)
KuaiRec: A Fully-observed Dataset for Recommender Systems (Density: Almost 100%) KuaiRec is a real-world dataset collected from the recommendation log
MarcoPolo is a clustering-free approach to the exploration of bimodally expressed genes along with group information in single-cell RNA-seq data
MarcoPolo is a method to discover differentially expressed genes in single-cell RNA-seq data without depending on prior clustering Overview MarcoPolo
Evaluation and Benchmarking of Speech Super-resolution Methods
Speech Super-resolution Evaluation and Benchmarking What this repo do: A toolbox for the evaluation of speech super-resolution algorithms. Unify the e
A benchmark for evaluation and comparison of various NLP tasks in Persian language.
Persian NLP Benchmark The repository aims to track existing natural language processing models and evaluate their performance on well-known datasets.
APEACH: Attacking Pejorative Expressions with Analysis on Crowd-generated Hate Speech Evaluation Datasets
APEACH - Korean Hate Speech Evaluation Datasets APEACH is the first crowd-generated Korean evaluation dataset for hate speech detection. Sentences of
Provide baselines and evaluation metrics of the task: traffic flow prediction
Note: This repo is adpoted from https://github.com/UNIMIBInside/Smart-Mobility-Prediction. Due to technical reasons, I did not fork their code. Introd
Tensorflow 1.13.X implementation for our NN paper: Wei Xia, Sen Wang, Ming Yang, Quanxue Gao, Jungong Han, Xinbo Gao: Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation. Neural Networks 145: 1-9 (2022)
Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation Simple implementation of our paper MVGC. The d
Frbmclust - Clusterize FRB profiles using hierarchical clustering, plot corresponding parameters distributions
frbmclust Getting Started Clusterize FRB profiles using hierarchical clustering,
Object detection evaluation metrics using Python.
Object detection evaluation metrics using Python.
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers Authors: Jaemin Cho, Abhay Zala, and Mohit Bansal (
Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations
TopClus The source code used for Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations, published in WWW 2022. Requ
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generative Transformers Authors: Jaemin Cho, Abhay Zala, and Mohit Bansal (
Company clustering with K-means/GMM and visualization with PCA, t-SNE, using SSAN relation extraction
RE results graph visualization and company clustering Installation pip install -r requirements.txt python -m nltk.downloader stopwords python3.7 main.
Implementation of SOMs (Self-Organizing Maps) with neighborhood-based map topologies.
py-self-organizing-maps Simple implementation of self-organizing maps (SOMs) A SOM is an unsupervised method for learning a mapping from a discrete ne
CLASSIX is a fast and explainable clustering algorithm based on sorting
CLASSIX Fast and explainable clustering based on sorting CLASSIX is a fast and explainable clustering algorithm based on sorting. Here are a few highl
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model About This repository contains the code to replicate the syn
Framework for Spectral Clustering on the Sparse Coefficients of Learned Dictionaries
Dictionary Learning for Clustering on Hyperspectral Images Overview Framework for Spectral Clustering on the Sparse Coefficients of Learned Dictionari
Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models Benchmark and Efficient Evaluation
Image-based Navigation in Real-World Environments via Multiple Mid-level Representations: Fusion Models Benchmark and Efficient Evaluation This reposi
python scripts to perform coin die clustering (performed on Riedones3D).
python scripts to perform coin die clustering (performed on Riedones3D).
Crypto Portfolio Clustering with and without optimization techniques (elbow method, PCA).
Crypto Portfolio Clustering Crypto Portfolio Clustering with and without optimization techniques (elbow method, PCA). Analysis This is an anlysis of c
DimReductionClustering - Dimensionality Reduction + Clustering + Unsupervised Score Metrics
Dimensionality Reduction + Clustering + Unsupervised Score Metrics Introduction
Nowadays we don't have time to listen to each and every song that we come across in a playlist.
Nowadays we don't have time to listen to each and every song that we come across in a playlist. so, this project helps you. we used Spotify API for collecting the dataset information and able to do EDA and used K- means clustering technique and created new playlists in Spotify again.
Evaluation framework for testing segmentation networks in PyTorch
Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!
clustering moroccan stocks time series data using k-means with dtw (dynamic time warping)
Moroccan Stocks Clustering Context Hey! we don't always have to forecast time series am I right ? We use k-means to cluster about 70 moroccan stock pr
This is the repository for our paper Ditch the Gold Standard: Re-evaluating Conversational Question Answering
Ditch the Gold Standard: Re-evaluating Conversational Question Answering This is the repository for our paper Ditch the Gold Standard: Re-evaluating C
FAIR Enough Metrics is an API for various FAIR Metrics Tests, written in python
☑️ FAIR Enough metrics for research FAIR Enough Metrics is an API for various FAIR Metrics Tests, written in python, conforming to the specifications
SuRE Evaluation: A Supplementary Material
SuRE Evaluation: A Supplementary Material This repository contains supplementary material regarding the evaluations presented in the paper Visual Expl
The open-source and free to use Python package miseval was developed to establish a standardized medical image segmentation evaluation procedure
miseval: a metric library for Medical Image Segmentation EVALuation The open-source and free to use Python package miseval was developed to establish
Official repository for the paper "On Evaluation Metrics for Graph Generative Models"
On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic
This repository contains pre-trained models and some evaluation code for our paper Towards Unsupervised Dense Information Retrieval with Contrastive Learning
Contriever: Towards Unsupervised Dense Information Retrieval with Contrastive Learning This repository contains pre-trained models and some evaluation
Clustering is a popular approach to detect patterns in unlabeled data
Visual Clustering Clustering is a popular approach to detect patterns in unlabeled data. Existing clustering methods typically treat samples in a data
Collections for the lasted paper about multi-view clustering methods (papers, codes)
Multi-View Clustering Papers Collections for the lasted paper about multi-view clustering methods (papers, codes). There also exists some repositories
Image Segmentation Evaluation
Image Segmentation Evaluation Martin Keršner, [email protected] Evaluation metrics for image segmentation inspired by paper Fully Convolutional Netw
On Evaluation Metrics for Graph Generative Models
On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic
SI_EXPLAINER_tg_bot: This bot is an assistant for medical professionals in interpreting the results of patient clustering.
SI_EXPLAINER_tg_bot This bot is an assistant for medical professionals in interpreting the results of patient clustering. ABOUT This chatbot was devel
This project has Classification and Clustering done Via kNN and K-Means respectfully
This project has Classification and Clustering done Via kNN and K-Means respectfully. It later tests its efficiency via F1/accuracy/recall/precision for kNN and Davies-Bouldin Index for Clustering. The Data is also visually represented.
Project made in Qt Designer + Python, for evaluation in the subject Introduction to Programming in IFPE - Paulista campus.
Project made in Qt Designer + Python, for evaluation in the subject Introduction to Programming in IFPE - Paulista campus.
NLG evaluation via Statistical Measures of Similarity: BaryScore, DepthScore, InfoLM
NLG evaluation via Statistical Measures of Similarity: BaryScore, DepthScore, InfoLM Automatic Evaluation Metric described in the papers BaryScore (EM
PyTorch code for the NAACL 2021 paper "Improving Generation and Evaluation of Visual Stories via Semantic Consistency"
Improving Generation and Evaluation of Visual Stories via Semantic Consistency PyTorch code for the NAACL 2021 paper "Improving Generation and Evaluat
[NeurIPS 2020] Official Implementation: "SMYRF: Efficient Attention using Asymmetric Clustering".
SMYRF: Efficient attention using asymmetric clustering Get started: Abstract We propose a novel type of balanced clustering algorithm to approximate a
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth
Instance segmentation by jointly optimizing spatial embeddings and clustering bandwidth This codebase implements the loss function described in: Insta
Python Machine Learning Jupyter Notebooks (ML website)
Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also
Practical Machine Learning with Python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
An Evaluation of Generative Adversarial Networks for Collaborative Filtering.
An Evaluation of Generative Adversarial Networks for Collaborative Filtering. This repository was developed by Fernando B. Pérez Maurera. Fernando is
A Java implementation of the experiments for the paper "k-Center Clustering with Outliers in Sliding Windows"
OutliersSlidingWindows A Java implementation of the experiments for the paper "k-Center Clustering with Outliers in Sliding Windows" Dataset generatio
Script and models for clustering LAION-400m CLIP embeddings.
clustering-laion400m Script and models for clustering LAION-400m CLIP embeddings. Models were fit on the first million or so image embeddings. A subje
TICC is a python solver for efficiently segmenting and clustering a multivariate time series
TICC TICC is a python solver for efficiently segmenting and clustering a multivariate time series. It takes as input a T-by-n data matrix, a regulariz
Python port of R's Comprehensive Dynamic Time Warp algorithm package
Welcome to the dtw-python package Comprehensive implementation of Dynamic Time Warping algorithms. DTW is a family of algorithms which compute the loc
The Turing Change Point Detection Benchmark: An Extensive Benchmark Evaluation of Change Point Detection Algorithms on real-world data
Turing Change Point Detection Benchmark Welcome to the repository for the Turing Change Point Detection Benchmark, a benchmark evaluation of change po
Clustering with variational Bayes and population Monte Carlo
pypmc pypmc is a python package focusing on adaptive importance sampling. It can be used for integration and sampling from a user-defined target densi
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 (
A Practitioner's Guide to Natural Language Processing
Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, Text Analytics with Python published by Apress/Springer.
K-Means Clustering and Hierarchical Clustering Unsupervised Learning Solution in Python3.
Unsupervised Learning - K-Means Clustering and Hierarchical Clustering - The Heritage Foundation's Economic Freedom Index Analysis 2019 - By David Sal
Machine learning library for fast and efficient Gaussian mixture models
This repository contains code which implements the Stochastic Gaussian Mixture Model (S-GMM) for event-based datasets Dependencies CMake Premake4 Blaz
Data and code from COVID-19 machine learning paper
Machine learning approaches for localized lockdown, subnotification analysis and cases forecasting in São Paulo state counties during COVID-19 pandemi
Automatic caption evaluation metric based on typicality analysis.
SeMantic and linguistic UndeRstanding Fusion (SMURF) Automatic caption evaluation metric described in the paper "SMURF: SeMantic and linguistic UndeRs
Text Summarization - WCN — Weighted Contextual N-gram method for evaluation of Text Summarization
Text Summarization WCN — Weighted Contextual N-gram method for evaluation of Text Summarization In this project, I fine tune T5 model on Extreme Summa
Mall-Customers-Segmentation - Customer Segmentation Using K-Means Clustering
Overview Customer Segmentation is one the most important applications of unsupervised learning. Using clustering techniques, companies can identify th
Benchmark spaces - Benchmarks of how well different two dimensional spaces work for clustering algorithms
benchmark_spaces Benchmarks of how well different two dimensional spaces work fo
News-Articles-and-Essays - NLP (Topic Modeling and Clustering)
NLP T5 Project proposal Topic Modeling and Clustering of News-Articles-and-Essays Students: Nasser Alshehri Abdullah Bushnag Abdulrhman Alqurashi OVER
Excel-report-evaluator - A simple Python GUI application to aid with bulk evaluation of Microsoft Excel reports.
Excel Report Evaluator Simple Python GUI with Tkinter for evaluating Microsoft Excel reports (.xlsx-Files). Usage Start main.py and choose one of the
Image Matching Evaluation
Image Matching Evaluation (IME) IME provides to test any feature matching algorithm on datasets containing ground-truth homographies. Also, one can re
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
An efficient PyTorch implementation of the evaluation metrics in recommender systems.
recsys_metrics An efficient PyTorch implementation of the evaluation metrics in recommender systems. Overview • Installation • How to use • Benchmark
GCRC: A Gaokao Chinese Reading Comprehension dataset for interpretable Evaluation
GCRC GCRC: A New Challenging MRC Dataset from Gaokao Chinese for Explainable Eva
Place holder for HOPE: a human-centric and task-oriented MT evaluation framework using professional post-editing
HOPE: A Task-Oriented and Human-Centric Evaluation Framework Using Professional Post-Editing Towards More Effective MT Evaluation Place holder for dat
Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)
Self-labelling via simultaneous clustering and representation learning 🆗 🆗 🎉 NEW models (20th August 2020): Added standard SeLa pretrained torchvis
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
Learning to Classify Images without Labels This repo contains the Pytorch implementation of our paper: SCAN: Learning to Classify Images without Label
Modeval (or Modular Eval) is a modular and secure string evaluation library that can be used to create custom parsers or interpreters.
modeval Modeval (or Modular Eval) is a modular and secure string evaluation library that can be used to create custom parsers or interpreters. Basic U
Modeval (or Modular Eval) is a modular and secure string evaluation library that can be used to create custom parsers or interpreters.
modeval Modeval (or Modular Eval) is a modular and secure string evaluation library that can be used to create custom parsers or interpreters. Basic U
Latte: Cross-framework Python Package for Evaluation of Latent-based Generative Models
Cross-framework Python Package for Evaluation of Latent-based Generative Models Latte Latte (for LATent Tensor Evaluation) is a cross-framework Python
Evaluation toolkit of the informative tracking benchmark comprising 9 scenarios, 180 diverse videos, and new challenges.
Informative-tracking-benchmark Informative tracking benchmark (ITB) higher diversity. It contains 9 representative scenarios and 180 diverse videos. m
Implementation for paper BLEU: a Method for Automatic Evaluation of Machine Translation
BLEU Score Implementation for paper: BLEU: a Method for Automatic Evaluation of Machine Translation Author: Ba Ngoc from ProtonX BLEU score is a popul
A Parameter-free Deep Embedded Clustering Method for Single-cell RNA-seq Data
A Parameter-free Deep Embedded Clustering Method for Single-cell RNA-seq Data Overview Clustering analysis is widely utilized in single-cell RNA-seque
Turning images into '9-pan' palettes using KMeans clustering from sklearn.
img2palette Turning images into '9-pan' palettes using KMeans clustering from sklearn. Requirements We require: Pillow, for opening and processing ima
Evaluation of file formats in the context of geo-referenced 3D geometries.
Geo-referenced Geometry File Formats Classic geometry file formats as .obj, .off, .ply, .stl or .dae do not support the utilization of coordinate syst
Training and Evaluation Code for Neural Volumes
Neural Volumes This repository contains training and evaluation code for the paper Neural Volumes. The method learns a 3D volumetric representation of
App customer segmentation cohort rfm clustering
CUSTOMER SEGMENTATION COHORT RFM CLUSTERING TỔNG QUAN VỀ HỆ THỐNG DỮ LIỆU Nên chuyển qua theme màu dark thì sẽ nhìn đẹp hơn https://customer-segmentat
Industrial Image Anomaly Localization Based on Gaussian Clustering of Pre-trained Feature
Industrial Image Anomaly Localization Based on Gaussian Clustering of Pre-trained Feature Q. Wan, L. Gao, X. Li and L. Wen, "Industrial Image Anomaly
Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs
Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs This repository contains code to accompany the paper "Hierarchical Clustering: O
An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022
Dual Correlation Reduction Network An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022. Any
The RDT protocol (RDT3.0,GBN,SR) implementation and performance evaluation code using socket
소켓을 이용한 RDT protocols (RDT3.0,GBN,SR) 구현 및 성능 평가 코드 입니다. 코드를 실행할때 리시버를 먼저 실행하세요. 성능 평가 코드는 패킷 전송 과정을 제외하고 시간당 전송률을 출력합니다. RDT3.0 GBN SR(버그 발견으로 구현중 입니
Predicting Baseball Metric Clusters: Clustering Application in Python Using scikit-learn
Clustering Clustering Application in Python Using scikit-learn This repository contains the prediction of baseball metric clusters using MLB Statcast
Evaluation toolkit of the informative tracking benchmark comprising 9 scenarios, 180 diverse videos, and new challenges.
Informative-tracking-benchmark Informative tracking benchmark (ITB) higher diversity. It contains 9 representative scenarios and 180 diverse videos. m
A PyTorch library and evaluation platform for end-to-end compression research
CompressAI CompressAI (compress-ay) is a PyTorch library and evaluation platform for end-to-end compression research. CompressAI currently provides: c
PyIOmica (pyiomica) is a Python package for omics analyses.
PyIOmica (pyiomica) This repository contains PyIOmica, a Python package that provides bioinformatics utilities for analyzing (dynamic) omics datasets.
Atari2600 Training / Evaluation with RLlib
Training Atari2600 by Reinforcement Learning Train Atari2600 and check how it works! How to Setup You can setup packages on your local env. $ make set
Official implementation of the paper "Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering"
Light Field Networks Project Page | Paper | Data | Pretrained Models Vincent Sitzmann*, Semon Rezchikov*, William Freeman, Joshua Tenenbaum, Frédo Dur
HDMapNet: A Local Semantic Map Learning and Evaluation Framework
HDMapNet_devkit Devkit for HDMapNet. HDMapNet: A Local Semantic Map Learning and Evaluation Framework Qi Li, Yue Wang, Yilun Wang, Hang Zhao [Paper] [
Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking and Jupyter notebook analysis.
sklearn-evaluation Machine learning model evaluation made easy: plots, tables, HTML reports, experiment tracking, and Jupyter notebook analysis. Suppo
Team collaborative evaluation tracker.
Team collaborative evaluation tracker.
Simple API for UCI Machine Learning Dataset Repository (search, download, analyze)
A simple API for working with University of California, Irvine (UCI) Machine Learning (ML) repository Table of Contents Introduction About Page of the
TextWorld is a sandbox learning environment for the training and evaluation of reinforcement learning (RL) agents on text-based games.
TextWorld A text-based game generator and extensible sandbox learning environment for training and testing reinforcement learning (RL) agents. Also ch
Label-Free Model Evaluation with Semi-Structured Dataset Representations
Label-Free Model Evaluation with Semi-Structured Dataset Representations Prerequisites This code uses the following libraries Python 3.7 NumPy PyTorch
Autoencoders pretraining using clustering
Autoencoders pretraining using clustering
Training and evaluation codes for the BertGen paper (ACL-IJCNLP 2021)
BERTGEN This repository is the implementation of the paper "BERTGEN: Multi-task Generation through BERT" (https://arxiv.org/abs/2106.03484). The codeb
clustimage is a python package for unsupervised clustering of images.
clustimage The aim of clustimage is to detect natural groups or clusters of images. Image recognition is a computer vision task for identifying and ve
Label-Free Model Evaluation with Semi-Structured Dataset Representations
Label-Free Model Evaluation with Semi-Structured Dataset Representations Prerequisites This code uses the following libraries Python 3.7 NumPy PyTorch