auroc

There are 0 repository under auroc topic.

Optimization-AI / LibAUC
LibAUC: A Deep Learning Library for X-Risk Optimization
auprc auroc contrastive-learning deep-learning machine-learning ndcg optimization pytorch ranking-algorithm self-supervised-learning
Language:Python 275
yzhuoning / LibAUC
(Archived). Please visit our new repo: https://github.com/Optimization-AI/LibAUC.
auc pytorch tensorflow auroc auprc auc-optimization imbalanced-datasets
75
yzhuoning / DeepAUC_OGB_Challenge
Top1 Solution on OGB Challenge (Graph Property Prediction on HIV dataset)
ogb auroc auc-optimization gcn drug-discovery molhiv
Language:Python 9
carpentries-incubator / machine-learning-novice-python
Introduction to Machine Learning with Python
lesson english pre-alpha carpentries-incubator machine-learning python bootstrapping data-leakage evaluation auroc prediction
Language:Python 4
liurui39660 / AUROC
Header-only AUROC/ROC-AUC in C++11
roc-auc auroc header-only
Language:C++ 4
Anitha-K-0711 / Customer_Conversion_Prediction_Project
Hi all! My project aims to predict customer conversion for an insurance company. The main objective of the project is to develop an accurate and efficient model that can aid the insurance company in improving its sales conversion rate and reducing marketing costs.
auroc datacleaning eda imbalanced-learning labelencoding matplotlib numpy pandas scikitlearn-machine-learning seaborn streamlit
Language:Jupyter Notebook 1
premchand9985 / Predicting_Incident_HeartFailure_Disease_Based-on-Transformers
This repository hosts a cutting-edge deep learning model developed to predict 6-month incident heart failure utilizing electronic health records (EHRs). Heart failure is a multifaceted medical condition characterized by its significant impact on patients' well-being and healthcare systems.
transformer-based-architecture deep-learning auroc ehr-data electronic-health-records transformers transformers-models predicting-heart-failure-incidence
Language:Python 1
EmmaSui / Classification--Predicting-Default-Risk
Classification prediction model
sklearn python classification logistic-regression decision-trees boosted-trees forest-models confusion-matrix precision roc auroc recall f1-score analytics prediction pandas
Language:Jupyter Notebook 0
lanmar / Python---Wine-quality
Cross-validation, knn classif, knn régression, svm à noyau, Ridge à noyau
cross-validation knn-classification knn standardization gridsearchcv python roc auroc knn-regression mse r2-score grid-search svm-kernel kernel-ridge kernel-svm kernel-svm-classifier kernel-ridge-regression
Language:Jupyter Notebook 0
merrillm1 / Ultimate_Challenge
Predicted rider retention for a taxi service and identified most significant factors that contributed to it. Achieved an 80% accuracy with a catboost model, which was chosen for its interpretability.
retention-analysis random-forest catboost feature-engineering feature-importance shap auroc accuracy
Language:Jupyter Notebook 0

auroc

Optimization-AI / LibAUC

yzhuoning / LibAUC

yzhuoning / DeepAUC_OGB_Challenge

carpentries-incubator / machine-learning-novice-python

liurui39660 / AUROC

Anitha-K-0711 / Customer_Conversion_Prediction_Project

premchand9985 / Predicting_Incident_HeartFailure_Disease_Based-on-Transformers

EmmaSui / Classification--Predicting-Default-Risk

lanmar / Python---Wine-quality

merrillm1 / Ultimate_Challenge