Search Results for "tuning"

...It includes summaries of supervised and unsupervised learning methods, model evaluation metrics (accuracy, precision, recall, ROC/AUC), overfitting/underfitting, regularization (L1/L2), cross-validation, feature engineering techniques, and perhaps tips for hyperparameter tuning. Each section is presented concisely, often with diagrams, formula snippets, and short explanatory notes to serve as quick reference for students, practitioners, or interview prep. The repository is ideal for those who want a compact, at-a-glance reminder of ML fundamentals without diving back into textbooks. Because the cheat sheet is meant to be portable and broadly useful, it is format-friendly (often in Markdown, PDF, or image formats) and easy to include in learning workflow or slides.

Teeser is a java-based integration framework for engineering emergent self-organizing behavior in distributed systems. It contains tools for analysis, tuning, macroscopic probing and simulations of distributed systems. Library of tools can be extended and everybody is encouraged to provide and share its tools with the community. The main idea is to provide application designers ability to seamlessly use tools which are helpful to design self-organizing behavior. Designers can continue to use their domain tools such as favorable simulator and by pluging it into the framework can take advantage of distributed simulations in the grid, various analyzers, optimizers (particle swarm optimization, genetic algorithms, ...). ...

The Parameter Tuning Unity (PTU) aims to adapt the parameters of ever connected multi-agents system, or expert system with a plugged optimization heuristic likes the descent of gradient for instance.