Cardiovascular Risk Prediction - Classification
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Updated
Aug 3, 2023 - Jupyter Notebook
Cardiovascular Risk Prediction - Classification
Binary classification of lumpy skin disease (imbalanced dataset) using ML algorithms in addition to oversampling/undersampling techniques.
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.
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
Classification of an imbalanced dataset using SMOTE oversampling technique and ML Algorithms - KNN , XGBoost and Naive Bayes classifier
A machine learning project on an imbalanced credit card data that detects fraudulent transactions.
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