Topic: "skewed-data"
ZhiningLiu1998/awesome-imbalanced-learning
😎 Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有关类别不平衡/长尾学习的一切：论文、代码、框架与库
Size: 213 KB - Last synced at: 12 days ago - Pushed at: 2 months ago - Stars: 1,433 - Forks: 228
grimmlab/permGWAS
Efficient Permutation-based GWAS for Normal and Skewed Phenotypic Distributions
Language: Python - Size: 13.8 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 24 - Forks: 3
atmacvit/bincrowd
Official Implementation of ACMMM'21 paper "Wisdom of (Binned) Crowds: A Bayesian Stratification Paradigm for Crowd Counting"
Language: Python - Size: 4.04 MB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 17 - Forks: 2
gmgeorg/LambertW
LambertW R package: Lambert W x F distributions and Gaussianization for skewed & heavy-tailed data
Language: R - Size: 341 KB - Last synced at: 3 months ago - Pushed at: over 1 year ago - Stars: 10 - Forks: 2
dataengi/spark-challenges
data engineering challenges and fun
Language: Scala - Size: 10.4 MB - Last synced at: over 1 year ago - Pushed at: almost 5 years ago - Stars: 7 - Forks: 7
rbnx/skewboost
Quantum ML for extremely imbalanced data
Language: Python - Size: 4.88 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 7 - Forks: 1
gmgeorg/pylambertw
pylambertw - sklearn interface to analyze and gaussianize heavy-tailed, skewed data
Language: Jupyter Notebook - Size: 1.17 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 6 - Forks: 1
Gelerion/spark-bin-packing-partitioner
Fix data skew by packing into bins
Language: Scala - Size: 1.18 MB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 5 - Forks: 0
karthik-d/few-shot-dermoscopic-image-analysis
Skin lesion image analysis that draws on meta-learning to improve performance in the low data and imbalanced data regimes.
Language: Python - Size: 738 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 4 - Forks: 2
fchamroukhi/MEteorits
Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIsTributionS
Language: R - Size: 28.3 MB - Last synced at: 12 days ago - Pushed at: about 5 years ago - Stars: 3 - Forks: 2
madhurimarawat/Data-Visualization-using-python
This repository contains data visualization programs on various datasets done using python.
Language: Jupyter Notebook - Size: 14.3 MB - Last synced at: about 1 month ago - Pushed at: 7 months ago - Stars: 1 - Forks: 2
ihdavjar/CSL2050_Major_Project
Course Major Project of Pattern Recognition and Machine Learning( CSL2050 )
Language: Jupyter Notebook - Size: 2.22 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0
ac12644/Fraud-Detection-AI
Build predictive models on highly skewed data by selecting an example of fraudulent transactions in the financial institutions🚀
Language: Jupyter Notebook - Size: 29.3 KB - Last synced at: about 2 months ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0
bharatc9530/Spam-Email-Classification
Language: Jupyter Notebook - Size: 3.04 MB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 0
vaitybharati/A8-Aczel-problems-practice-1-48-1-51-1-53-
Language: Jupyter Notebook - Size: 9.77 KB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 0
charumakhijani/advanced-house-price-prediction
Language: Jupyter Notebook - Size: 1.66 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 1
sushant1827/Finding-Donors-for-Charity-using-Machine-Learning
Machine Learning Nano-degree Project : To help a charity organization identify people most likely to donate to their cause
Language: Jupyter Notebook - Size: 792 KB - Last synced at: 30 days ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 1
gaju-01/ClientPulse
This is a data mining model to predict client behavior within an organization, enabling better alignment with client needs. The model determines whether clients are likely to churn using advanced data preprocessing and imbalanced learning techniques. The dataset for this analysis was sourced from Kaggle.
Language: Jupyter Notebook - Size: 1.28 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0
LKEthridge/SDA_Project
A Statistical Data Analysis project from TripleTen
Language: Jupyter Notebook - Size: 2.8 MB - Last synced at: about 1 month ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0
Daniel-Carpenter/Delivery-Service-ETA-Prediction 📦
Predicting Time of Arrival for Food Delivery Service
Language: R - Size: 69 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 1
AbbasElHachem/qcpcp
Space-Time Statistical Quality Control of Extreme Precipitation Observation
Language: Python - Size: 9.62 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
MathCortes/Projeto7-WineSamples-ML_Clustering
A base possui informações obtidas de análises químicas de vinhos da mesma região da Itália, porém são provenientes de 3 diferentes cultivadores. A análise mostra a quantidade de 13 componentes achados em cada um dos 3 tipos de vinhos.
Language: Jupyter Notebook - Size: 2.25 MB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0
SmartNamDevoloper/Telecom_Customer_churn_Classification
This project demonstrates building a classification model for imbalanced data. Feature engineering, feature selection and extensive EDA. Comparing of logistic regression, random forest and ADA Boost models are done before finalizing the best model.
Language: Jupyter Notebook - Size: 5.23 MB - Last synced at: almost 2 years ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0
MateJozsaPhys/CNDinvestigation
Opportunities and challenges in partitioning the graph measure space of real-world networks
Language: Jupyter Notebook - Size: 7.82 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0
north0n-FI/Predicting-Fraud-in-Financial-Payment-Services
Trying to recogize and predict fraud in financial transactions is a good example of binary classification analysis. A transaction either is fraudulent, or it is genuine. What makes fraud detection especially challenging is the is the highly imbalanced distribution between positive (genuine) and negative (fraud) classes.
Language: Jupyter Notebook - Size: 1000 KB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 0 - Forks: 0
