Abstract: Silk quality is a critical determinant in the silk industry, significantly influencing the market value of silk products. This study proposes an innovative method for forecasting silk ...

Objective: To develop the extreme gradient boosting (XG Boost) machine learning (ML) model for predicting gestational diabetes mellitus (GDM) compared with a model using the traditional logistic ...

Machine Learning , Python , K-Mean Algorithm , Xg Boost, Rondom Forest Algorithm ,Data Collection , Data Validation , Data Transformation ,Clustering ,Model Tuning , Best Model for Each Cluster, ...

This project uses XGBoost — a powerful and scalable machine learning algorithm — to predict Air Quality Index (AQI) from atmospheric pollutant data. XGBoost outperforms traditional models by using ...