This project was completed as part of the CIT 650 "Intro To Big Data" course at Nile University.
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Updated
May 24, 2024 - Jupyter Notebook
This project was completed as part of the CIT 650 "Intro To Big Data" course at Nile University.
Efficient Permutation-based GWAS for Normal and Skewed Phenotypic Distributions
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
pylambertw - sklearn interface to analyze and gaussianize heavy-tailed, skewed data
Skin lesion image analysis that draws on meta-learning to improve performance in the low data and imbalanced data regimes.
This repository contains data visualization programs on various datasets done using python.
LambertW R package: Lambert W x F distributions and Gaussianization for skewed & heavy-tailed data
Course Major Project of Pattern Recognition and Machine Learning( CSL2050 )
Predicting Time of Arrival for Food Delivery Service
Space-Time Statistical Quality Control of Extreme Precipitation Observation
Build predictive models on highly skewed data by selecting an example of fraudulent transactions in the financial institutions🚀
Official Implementation of ACMMM'21 paper "Wisdom of (Binned) Crowds: A Bayesian Stratification Paradigm for Crowd Counting"
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.
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.
Opportunities and challenges in partitioning the graph measure space of real-world networks
Mixtures-of-ExperTs modEling for cOmplex and non-noRmal dIsTributionS
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