adasyn
There are 37 repositories under adasyn topic.
yazanobeidi/fraud-detection
Credit Card Fraud Detection using ML: IEEE style paper + Jupyter Notebook
Tek-nr/AI-Based-Fraud-Detection
A fraud detection project that processes user or credit card data using machine learning and deep learning algorithms.
Ashutosh27ind/PGDDS-Capstone-Project
Credit Card Fraud Detection Project
antorguez95/synthetic_data_generation_framework
This repository contains the code of our published work in IEEE JBHI. Our main objective was to demonstrate the feasibility of the use of synthetic data to effectively train Machine Learning algorithms, prooving that it benefits classification performance most of the times.
ChaitanyaC22/Fraud_Analytics_Credit_Card_Fraud_Detection
The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.
denistanjingyu/LTA-Mobility-Sensing-Project
Location information about commuter activities is vital for planning for travel disruptions and infrastructural development. The Mobility Sensing Project aims to find innovative and novel ways to identify travel patterns from GPS data and other multi-sensory data collected in smartphones. This will be transformative to provide personalised travel information.
sumitsomans/EigenSample
MATLAB code for augmenting small datasets using EigenSample
alhomayani/Oversampling_BLE_fingerprints
The computing scripts associated with our paper entitled "Oversampling Highly Imbalanced Indoor Positioning Data using Deep Generative Models".
kostadin-georgiev97/ct5129_dyslexia
This repository contains the code for baseline model replication along with all experiments and used datasets as part of the master's thesis on the topic "Detecting Dyslexia Using Deep Learning".
mcarpanelli/Fraud-Prediction
Data Science Case Study
Ashutosh27ind/census_income_prediction
The case study is a traditional supervised binary classification problem based on the UCI Machine Learning Repository "adult" dataset.
domingosdeeulariadumba/MarketingCampaignPrediction2
Continuing with telemarketing model to predict campaign subscriptions in a portuguese bank institution. For this project I have evaluated the performance of four resampling techniques and selected the best one to implement the logistic model.
hase3b/Class-Imbalance-Classification-Performance-Analysis
This repository contains the code, documentation, and datasets for a comprehensive exploration of machine learning techniques to address class imbalance. The project investigates the impact of various methods, like ADASYN, KMeansSMOTE, and Deep Learning Generator, on classification performance while effectively demonstrating benefits of pipelining.
masjidilaqsha/obesity-status-in-indonesia-2013
Classify Indonesian Obesity Status using ADASYN-N and Random Forest algorithm
MicheleDiSabato/detecting-abnormal-markets-ews
Detecting Abnormal Markets - Early Warning Systems
shanuhalli/Assignment-Random-Forest
Use Random Forest to prepare a model on fraud data. Treating those who have taxable income <= 30000 as "Risky" and others are "Good" and A cloth manufacturing company is interested to know about the segment or attributes causes high sale.
SimarjotKaur/Customer-Churn-Prediction
To predict whether the customers will subscribe to the system after 1-month free trial or not.
Yoris95/Classification-of-Obesity-Status-in-Indonesia-Using-XGBoost-and-ADASYN-N-Method
Classification of Obesity Status in Indonesia Using XGBoost & ADASYN-N Method
adityabhardwaj27/NAFLD_PredictionSystem
Led a project to predict Non-Alcoholic Fatty Liver Disease (NAFLD) using machine learning.
Al-1n/Gradient_Boosting_Tuning
Evaluating Hyperopt, Optuna, and TunedThresholdClassifierCV
Amber-shekh/Handling-Imbalance-data
This repository will compare the performance of different classification algorithms on various imbalanced datasets using multiple balancing techniques.
at-akshat-2107/Credit-Card-Fraud-Detection-Capstone-Project-EPGP
In this Upgrad/IIIT-B Capstone project, we navigated the complex landscape of credit card fraud, employing advanced machine learning techniques to bolster banks against financial losses. With a focus on precision, we predicted fraudulent credit card transactions by analyzing customer-level data from Worldline and the Machine Learning Group.
deepakrameshgowda/CREDIT-CARD-FRAUD-DETECTION
Building predictive models to detect and prevent the fraudulent transactions happening on cerdit cards and debit cards. Implementation of 2nd factor authentication for safe and secure transactions.
egorumaev/2022-bank-customers-churn
Предсказание оттока клиентов из банка
hasanzeynal/Resampling-Techniques-For-Imbalance-Problems
The Repository is created to cover undersampling and oversampling methods to deal imbalance problem.
HeliJulia/AML-Risk-Group-Prediction
Acute Myeloid Leukemia Risk Group Prediction from Gene Expression Data with Feed-Forward Neural Networks
manujbsharma/Credit_Card-Fraud_Detection
The aim of this project is to predict fraudulent credit card transactions using machine learning models.
power-TY/Imbalnce_Handling_PySpark
PySpark를 이용한 불균형 데이터 처리 알고리즘 구현
sssingh/credit-card-fraud-detection
Build, train and compare performances of multiple binary classification machine learning model techniques to detect credit card fraudulent transactions.
Yoonyoung-Cho/HR_Data_predicting_employee_resignition_2019
2019.12.12 개인 프로젝트. 직원의 퇴사를 예측하고 퇴사 이유 및 해결방안 제시
arunku825/Credit-Card-Fraud-Detection
Developed a model to classify fraud transactions.
saikrishnabudi/Random-Forest
Data Science - Random Forest Work
Silvano315/Health-Insurance-Prediction
This repository aims to test some machine learning and ELI5 explainability technique in order to predict whether the customer would be interested in Vehicle insurance, you have information about demographics, vehicles, policy