📘 This repository predicts OLA driver churn using ensemble methods—Bagging (Random Forest) and Boosting (XGBoost)—with KNN imputation and SMOTE. It reveals city-wise churn trends and key performance ...

Abstract: Measuring the equivalence ratio using flame spectral data is a key focus in combustion diagnostic techniques. Traditional methods rely on chemiluminescent bands with distinct spectral ...

52 The study examined multiple algorithms and found that the bagging ensemble that evaluated clinical symptoms performed the best, followed by neural network, support vector machine and linear ...

This study proposes a hybrid ensemble classification algorithm that leverages Penalized Matrix Decomposition (PMD) for feature extraction and a bagging approach using a Support Vector Machine (SVM), ...

A java application to guide the modeling process using a best-first search algorithm. The application uses a set of machine learning algorithms to generate models and evaluate them using a ...

We chose 10 ML algorithms for prediction, including linear regression (LR), ridge regression (RR), Lasso ... and the personalized prediction of each sample. The flowchart of the process is shown in ...