Crate friedrich[][src]

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Friedrich : Gaussian Process Regression

This libarie implements Gaussian Process Regression in Rust. Our goal is to provide a building block for other algorithms (such as Bayesian Optimization).

Gaussian process have both the ability to extract a lot of information from their training data and to return a prediction and an uncertainty on their prediction. Furthermore, they can handle non-linear phenomenons, take uncertainty on the inputs into account and encode a prior on the output.

All of those properties make them an algorithm of choice to perform regression when data is scarce or when having uncertainty bars on the ouput is a desirable property.

However, the o(n^3) complexity of the algorithm makes the classical implementation unsuitable for large training datasets.


This implementation lets you :

  • define a gaussian process with default parameters or using the builder pattern
  • train it on multidimensional data
  • fit the parameters (kernel, prior and noise) on the training data
  • add additional samples efficiently (O(n^2)) and refit the process
  • predict the mean, variance and covariance matrix for given inputs
  • sample the distribution at a given position
  • save and load a trained model with serde


Most methods of this library can currently work with the following input -> ouput pairs :

  • Vec<f64> -> f64 a single, multidimensional, sample
  • Vec<Vec<f64>> -> Vec<f64> each inner vector is a training sample
  • DMatrix<f64> -> DVector<f64> using a nalgebra matrix with one row per sample
  • ArrayBase<f64, Ix1> -> f64 a single sample stored in a ndarray array (using the friedrich_ndarray feature)
  • ArrayBase<f64, Ix2> -> Array1<f64> each row is a sample (using the friedrich_ndarray feature)

See the Input trait if you want to add you own input type.


Gaussian process




Implemented by Input -> Output type pairs

Type Definitions

matrix with arbitrary storage S: Storage<f64, Dynamic, Dynamic>

row vector with arbitrary storage S: Storage<f64, U1, Dynamic>

vector with arbitrary storage S: Storage<f64, Dynamic, U1>