A multi-class classification model is a model that can distinguish between more than two classes, such as red, green, or blue, dog, cat, or bird, etc.

This project demonstrates a machine learning pipeline for multi-class classification using XGBoost and Random Forest models. The pipeline includes data preprocessing, feature selection, data balancing ...

Creating the Neural Network Model Creating the multi-class classification neural network model is simultaneously simple and complicated. ... Like many scikit models, the MLPClassifier class has a lot ...

The model summary includes all the layers, trainable parameters, and architecture, showing how MobileNetV2 is extended for multi-class classification. 🎯 Conclusion: This project successfully ...

For a variety of applications, including environmental monitoring, biodiversity studies, and historical happenings, it is essential to accurately describe maritime items. In this study, a multi-class ...

The Data Science Lab. Multi-Class Classification Using a scikit Decision Tree. Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the ...

The Data Science Lab. Multi-Class Classification Using LightGBM. Dr. James McCaffrey of Microsoft Research provides a full-code, step-by-step machine learning tutorial on how to use the LightGBM ...