Validation methods for the GeoStats.jl framework

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A package for plotting custom symbols from Taija packages.

Efficient Global Optimization (EGO) Toolbox

The Julia Implementation of Gradient Boosting.

Unified framework of quantification and unfolding algorithms

Implementations of various Relief-based algorithms in Julia

Robustness-inducing transformations for sparse partial least squares

External Machine Learning Libs for TSML

Implementation of Gaussian mixture regression model in Julia.

Julia package for the paper "Decomposition with Monotone B-splines: Fitting and Testing"

Explores representations based on bag words

Machine Learning Suite for Julia

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A Julia package for multiple kernel learning based one-class support vector machine.

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Genomic offset statistics

Approximation Package for High-Dimensional Functions in Julia

A Julia package for simulation, verification and parameter estimation of Biochemical Networks with Approximate Bayesian Computation (ABC) methods.

This is a dimensionality reduction algorithm which has the goal of maintaining interpretability i.e we eliminate variables directly from potential models that don't seem to add any predictive power.

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Adds support for parallelization for Taija packages.