There are 0 repository under smote-sampling topic.
Machine learning model for Credit Card fraud detection
Spam detection in SMS messages with BERT model and Machine Learning algorithms
Electricity Fraud Detection in Smart Grids
System to tell apart the transaction was from the real user who owns the credit card or the transaction was from the stolen credit card.
The aim to decrease the maintenance cost of generators used in wind energy production machinery. This is achieved by building various classification models, accounting for class imbalance, and tuning on a user defined cost metric (function of true positives, false positives and false negatives predicted) & productionising the model using pipelines.
Predict the enzyme class of a given FASTA sequence using deep learning methods including CNNs, LSTM, BiLSTM, GRU, and attention models along with a host of other ML methods.
Predicting the ability of a borrower to pay back the loan through Traditional Machine Learning Models and comparing to Ensembling Methods
A compilation of codes for SMA, DC, ADS
Credit Card fraud detection
使用比赛方提供的脱敏数据,进行客户信贷流失预测。
Repository for "Data Mining - Advanced Topics and Applications" projects exam.
Obstructive Sleep Apnea classification with help of numerical data set which having the physical body characteristics with the help of machine learing
Prediction of basic soil nutrients (phosphorus, potassium, boron, calcium, magnesium and manganese) using reflectance from Hyperspectral Satellite Images (HSI).
A model that recommends University based on details of an applicant.
Gear detection using OpenCv and Machine Learning
RCSMOTE: Range-Controlled Synthetic Minority Over-sampling Technique for handling the class imbalance problem
This project provides a comprehensive analysis of the Eurovision Song Contest, with insights derived from both traditional statistical methods and machine learning techniques.
This is a program to predict the possible risk of default on credit card use.
Course Project for CS273A: Machine Learning at UCI
This project is a part of the research on PolyCystic Ovary Syndrome Diagnosis using patient history datasets through statistical feature selection and multiple machine learning strategies. The aim of this project was to identify the best possible features that strongly classifies PCOS in patients of different age and conditions.
Bank bankruptcy predictions on FDIC bank failure data using tensorflow, keras, sklearn, ensemble, and imblearn libraries.
This small repository contains the SMOTE implementation from scratch.
Binary classification of lumpy skin disease (imbalanced dataset) using ML algorithms in addition to oversampling/undersampling techniques.
Predict whether customer purchase a product or not in a session
Project is about predicting Class Of Beans using Supervised Learning Models
This project was made as a final project at Rakamin Academy in collaboration with ID/X Partner.
12 clinical features for predicting death events.
• Did in depth exploratory data analysis on the churn dataset and got valuable insight for the machine learning model. • Created a machine learning model using a bunch of algorithms (LR, KNN, SVC, Random Forest, Gradient Boosting) to predict customer churn based on historical data.GB classifier achieved 8% decrease in the overall churn rate
Maintaining the privacy of local server data in a federated learning framework using differential privacy by TensorFlow Privacy Library.
Different models to detect if a claim is fraudulent or not
Predicting the churn of customers in a Telecom company using classification algorithms.
Source code for "Cross-project Defect Prediction with An Enhanced Transfer Boosting Algorithm"