Cardiovascular Risk Prediction - Classification
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Updated
Aug 3, 2023 - Jupyter Notebook
Cardiovascular Risk Prediction - Classification
Predict CHD Risk with Precision: This machine learning model analyzes patient demographics, behaviors, and medical factors to accurately predict the likelihood of developing coronary heart disease within the next 10 years.
Binary classification of lumpy skin disease (imbalanced dataset) using ML algorithms in addition to oversampling/undersampling techniques.
Developing a Classification Model for Predicting Credit Card Default
Does the amount of screen time a person spends at age 16 affect their levels of depression and anxiety at age 18?
DAEB-τSS3: Imbalanced Social Media Text Depression Detection Method
EfficientNetV2 (Efficientnetv2-b2) and quantization int8 and fp32 (QAT and PTQ) on CK+ dataset . fine-tuning, augmentation, solving imbalanced dataset, etc.
2022년 1학기 개인 프로젝트 : 뇌졸증 환자 예측 모델·분석
Binary classification, SHAP (Explainable Artificial Intelligence), and Grid Search (for tuning hyperparameters) using EfficientNetV2-B0 on Cat VS Dog dataset.
OBEBS method
A machine learning project on an imbalanced credit card data that detects fraudulent transactions.
Classification of an imbalanced dataset using SMOTE oversampling technique and ML Algorithms - KNN , XGBoost and Naive Bayes classifier
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