Welcome to the iOpt documentation!
iOpt is an open source framework for automatic selection of parameter values both for mathematical models of complex industrial processes and for AI and ML methods used in industry. The framework is distributed under the 3-Clause BSD license.
Key features of the framework
Automatic selection of parameter values both for mathematical models and for AI and ML methods used in industry.
Intelligent control of the process of choosing the optimal parameters for industrial applications.
Integration with external artificial intelligence and machine learning libraries or frameworks as well as applied models.
Automation of the preliminary analysis of the models under study, e.g., by identifying different types of model dependencies on different groups of parameters.
Visualization of the process of choosing optimal parameters.
Content:
- Introduction
- Installation and how to use
- Examples of using
- Tuning the parameters of a genetic algorithm to solve the traveling salesman problem
- Tuning support vector machine hyperparameters for a classification problem in machine learning
- Tuning hyperparameters of the support vector machine for the problem of classifying the state of the air pressure system of trucks
- Tuning hyperparameters in the problem of predicting the concentration of nitrogen oxide in the working area of a gas turbine
- Tuning mixed hyperparameters using the iOpt framework for the problem of predicting the concentration of nitrogen oxide in the working area of a gas turbine
- Tuning hyperparameters in the problem of analyzing and predicting the state of power transformers of nuclear power plants
- Tuning mixed hyperparameters using the iOpt framework
- iOpt
- About us