nested-cross-validation

Ensemble Integration: a customizable pipeline for generating multi-modal, heterogeneous ensembles

Nested Cross-Validation for Bayesian Optimized Gradient Boosting

Experimenting with various implementations and methods of nested cross-validation in R and Python

Nested Cross-Validation for Bayesian Optimized Linear Regularization

Python package customizing nested cross validation for tabular data.

Using scikit-learn RandomizedSearchCV and cross_val_score for ML Nested Cross Validation

A Knn algorithm used for train a model and prediction

Internally validated 30-day mortality prediction after acute myocardial infarction using ridge logistic regression, repeated nested cross-validation, calibration, bootstrap uncertainty and decision-curve analysis.

End-to-end MLOps pipeline predicting corporate bankruptcy from 95 financial ratios. Features nested CV, SHAP explainability, MLflow tracking, and Dockerized FastAPI deployment.

Implementation of (Kernel) Ridge Regression predictors from scratch on Kaggle's Spotify Tracks Dataset.

Python implementation of a nested cross-validation pipeline compatible with scikit-learn API.

Predicting UK residential retrofit potential from EPC open data using Random Forest, XGBoost, Logistic Regression and SVM under nested cross-validation

❤️ 🩸 Blood test classifier for infected COVID-19 patients using xgb, catboost, rf and lr

nestkit: a nested cross-validation toolkit for scikit-learn

🚀 Optimize TensorFlow models with the Nested Learning Optimizer for improved performance, faster convergence, and enhanced training stability.

Nested cross-validation study with Pearson correlation feature selection for breast cancer classification, reporting unbiased generalization estimates.

Predict antidepressant (SSRI) response from resting-state EEG

Multiclass sentiment analysis on Amazon product reviews using lexicon-based and machine learning models, including AFINN, TF-IDF + XGBoost with nested cross-validation.

End-to-end resting-state EEG pipeline classifying younger (20-34) vs. older (52-70) adults from 405 people in OpenNeuro ds005385: MNE-Python preprocessing, Welch spectral features and nested cross-validated gradient boosting (ROC AUC 0.90, permutation p < 0.01).