yuhung1206/Gaussian-Process-for-Regression
Implementation of Guassion Process (GP) for regreesion with the exponential-quadratic kernel function.
This project helps you predict an outcome (target 't') based on a related input ('x'), even with limited data points. You provide existing pairs of inputs and their known outcomes, and it generates predictions for new inputs, along with an understanding of how confident those predictions are. This is useful for scientists, engineers, or researchers who need to model relationships and make predictions when exact formulas aren't known.
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Use this if you have a dataset with pairs of an input and its corresponding output, and you need to predict outputs for new inputs, especially when you also want to understand the uncertainty of those predictions.
Not ideal if you have a massive dataset or require extremely fast predictions, as Gaussian Processes can be computationally intensive.
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Language
MATLAB
License
MIT
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Last pushed
Sep 08, 2021
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