ILaskira/Soaring-Stock-Prediction-Challenge

Competition project for classifying soaring stocks using XGBoost and stacking-based ensemble with advanced feature selection and threshold tuning.

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LEANDERANTONY/Credit_Card_Fraud_Detection

Detecting fraudulent transactions from real-world anonymized credit card data using XGBoost and SMOTE. Achieved 97%+ ROC-AUC on a highly imbalanced dataset.

Language: Jupyter Notebook - Size: 1.22 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

adabyt/imbalanced-data-techniques

Dealing with Imbalanced Datasets in Binary Classification: A Comparative Study of Resampling and Ensemble Methods

Language: Python - Size: 9.77 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

AdibahR/Indohome-telco-churn-app

IndoHome Telco Churn Prediction System - Comprehensive ML project with Streamlit deployment, Tableau analytics, and end-to-end data science pipeline for telecommunications customer retention

Language: Python - Size: 140 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

KhushiRajurkar/Exoplanet-Habitability-Prediction-Model

Predicts whether an exoplanet is habitable using ML. Handles class imbalance with ADASYN, tests multiple models, and saves the best one. Includes confusion matrices, ROC curves, and a clean Jupyter notebook

Language: Jupyter Notebook - Size: 7.7 MB - Last synced at: about 2 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

havva-nur-ezginci/Diabetes-EyeDisease-Detection-ML-DL

💻This project involves the application of machine learning and deep learning methods 📊 to detect diabetes🩸 and diabetes-related eye 👁️diseases.

Language: Jupyter Notebook - Size: 5.87 MB - Last synced at: 5 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

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.

Language: Jupyter Notebook - Size: 67.3 MB - Last synced at: 5 months ago - Pushed at: over 2 years ago - Stars: 5 - Forks: 2

KhushiRajurkar/Exoplanet-Habitability-Prediction Fork of SauravSJK/Exoplanet-Habitability-Prediction

Using the PHL Data to predict the habitability of an exoplanet

Language: Python - Size: 15.6 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0

juliuszlosinski/Imbalanced-Data-Problem-for-Image-Detection-One-Stage-Detectors

Implementation of augmentation, SMOTE, ADASYN, AE, DGAN for oversampling image data used in detection (YOLO and others one stage detectors). Maritime flags/code scenario.

Language: Python - Size: 2.76 GB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

msikorski93/Credit-Card-Fraud-Detection

A binary classification task performed with machine learning in Python. The dataset's target distribution is heavily imbalanced. The model performance was evaluated with F1 scores.

Language: Jupyter Notebook - Size: 1.81 MB - Last synced at: 6 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 0

apurvanand-2002/Dealing-with-imbalanced-data

Using Random undersampling, Tomeklinks, Random oversampling, SMOTE, SMOTE+Tomeklinks and ADASYN from inbuilt imbalanced learn library and found how many records added or discarded.

Language: Jupyter Notebook - Size: 135 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 1 - Forks: 0

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.

Language: Jupyter Notebook - Size: 6.88 MB - Last synced at: 5 months ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 1

Yoonyoung-Cho/HR_Data_predicting_employee_resignition_2019

2019.12.12 개인 프로젝트. 직원의 퇴사를 예측하고 퇴사 이유 및 해결방안 제시

Language: Jupyter Notebook - Size: 4.12 MB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

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.

Language: Python - Size: 36.9 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 5 - Forks: 1

power-TY/Imbalnce_Handling_PySpark

PySpark를 이용한 불균형 데이터 처리 알고리즘 구현

Language: Jupyter Notebook - Size: 43 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

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

Language: Jupyter Notebook - Size: 18.6 MB - Last synced at: 6 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Ashutosh27ind/census_income_prediction

The case study is a traditional supervised binary classification problem based on the UCI Machine Learning Repository "adult" dataset.

Language: Jupyter Notebook - Size: 3.98 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

manujbsharma/Credit_Card-Fraud_Detection

The aim of this project is to predict fraudulent credit card transactions using machine learning models.

Language: Jupyter Notebook - Size: 3.66 MB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0

Ashutosh27ind/PGDDS-Capstone-Project

Credit Card Fraud Detection Project

Language: Jupyter Notebook - Size: 67.1 MB - Last synced at: over 1 year ago - Pushed at: about 5 years ago - Stars: 7 - Forks: 12

saikrishnabudi/Random-Forests

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.

Language: Jupyter Notebook - Size: 4.74 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

Tek-nr/AI-Based-Fraud-Detection

A fraud detection project that processes user or credit card data using machine learning and deep learning algorithms.

Language: Jupyter Notebook - Size: 18 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

alhomayani/Oversampling_BLE_fingerprints

The computing scripts associated with our paper entitled "Oversampling Highly Imbalanced Indoor Positioning Data using Deep Generative Models".

Language: Python - Size: 24.4 KB - Last synced at: almost 2 years ago - Pushed at: about 4 years ago - Stars: 2 - Forks: 0

sumitsomans/EigenSample

MATLAB code for augmenting small datasets using EigenSample

Language: MATLAB - Size: 197 KB - Last synced at: almost 2 years ago - Pushed at: over 5 years ago - Stars: 3 - Forks: 1

Yoris95/Classification-of-Obesity-Status-in-Indonesia-Using-XGBoost-and-ADASYN-N-Method

Classification of Obesity Status in Indonesia Using XGBoost & ADASYN-N Method

Language: R - Size: 69.3 KB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

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.

Language: Python - Size: 976 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

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".

Language: Jupyter Notebook - Size: 1.04 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

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.

Language: Jupyter Notebook - Size: 7.71 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

sssingh/credit-card-fraud-detection

Build, train and compare performances of multiple binary classification machine learning model techniques to detect credit card fraudulent transactions.

Language: Jupyter Notebook - Size: 1.91 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

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.

Language: Jupyter Notebook - Size: 2.82 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

yazanobeidi/fraud-detection

Credit Card Fraud Detection using ML: IEEE style paper + Jupyter Notebook

Language: Jupyter Notebook - Size: 68 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 82 - Forks: 36

mcarpanelli/Fraud-Prediction

Data Science Case Study

Language: Python - Size: 462 KB - Last synced at: over 2 years ago - Pushed at: about 7 years ago - Stars: 2 - Forks: 3

MicheleDiSabato/detecting-abnormal-markets-ews

Detecting Abnormal Markets - Early Warning Systems

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LuckyWirasakti/machine-learning-toolbox

Language: Jupyter Notebook - Size: 36.1 KB - Last synced at: over 2 years ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 0

LuckyWirasakti/Adaptive-Synthetic

Language: HTML - Size: 5.54 MB - Last synced at: over 2 years ago - Pushed at: almost 5 years ago - Stars: 0 - Forks: 0

rajtulluri/Santander-Customer-transaction-prediction

Predicting whether a customer will carry out a transaction or not for Santander group

Language: Jupyter Notebook - Size: 107 KB - Last synced at: over 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0

SimarjotKaur/Customer-Churn-Prediction

To predict whether the customers will subscribe to the system after 1-month free trial or not.

Language: Jupyter Notebook - Size: 218 KB - Last synced at: 3 months ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 0