Multivariate Optimization Library in Ruby. Mopti supports Nelder-Mead simplex method and Scaled Conjugate Gradient.

Extracts data from a double precision floating point binary file. 倍精度浮動小数点バイナリファイルからデータを抽出するよ。

NetAnalyzer is a useful network analysis tool developed in Ruby that can 1) analyse any type of unweighted network, regardless of the number of layers, 2) calculate the relationship between different layers, using various association indices (Jaccard, Simpson, PCC, geometric, cosine and hypergeometric) and 3) validate the results

neural network ruby implementaiton

Rubyでニューラルネットワークを作成できます。

Read binary files and handle them with `NArray`.

Numo::FFTW development version.

Numo::Liblinear is a Ruby gem binding to the LIBLINEAR library. LIBLINEAR is one of the famous libraries for large-scale regularized linear classification and regression. Numo::Liblinear makes to use the LIBLINEAR functions with dataset represented by Numo::NArray.

Numo::Libsvm is a Ruby gem binding to the LIBSVM library. LIBSVM is one of the famous libraries that implemented Support Vector Machines, and provides functions for support vector classifier, regression, and distribution estimation. Numo::Libsvm makes to use the LIBSVM functions with dataset represented by Numo::NArray.

Numo::Linalg.randsvd is a module function on Numo::Linalg for truncated singular value decomposition with randomized algorithm.

Numo::Pocketfft provides functions for descrete Fourier Transform based on pocketfft.

Numo::Random provides random number generation with several distributions for Numo::NArray.

Numo::TinyLinalg is a subset library from Numo::Linalg consisting only of methods used in Machine Learning algorithms. The functions Numo::TinyLinalg supports are dot, det, eigh, inv, pinv, qr, solve, cholesky, cho_solve and svd.

Automatically generate Ruby code from ONNX

A lightweight Ruby library designed to provide quick evaluation of option strategies.

PETS suite includes three different tools. CohortAnalyzer performs the calculation of several statistics that gives an overview of a cohort of patients to analyse. Reg2Phen uses associations between pathological phenotypes and regions of the genome (these associations can be calculated from the cohort of patients if they include genotypic & phenotypic information using NetAnalyzer, another Ruby gem) to find, for a given genomic region, which pathological phenotypes have been associated with that region. The third tool, Phen2Reg, is a predictor that using the same associations as Reg2Phen, predicts which genomic regions can be the cause of a list of pathological phenotypes observed in a patient.

rblearn (ruby-learn) provides methods for feature extracting and some algorithms.

Red Arrow Numo::NArray adds `Arrow::Tensor#to_narray` and `#to_arrow`/`#to_arrow_array` to `Numo::NArray`'s numerical subclasses such as `Numo::Int8`. `Arrow::Tensor#to_narray` returns a `Numo::NArray`'s numerical subclass such as `Numo::Int8`. `#to_arrow` returns a `Arrow::Tensor`. `#to_arrow_array` returns an `Arrow::Array` instance if the original object is an 1 dimensional array.

Red Datasets Numo::NArray adds `#to_narray` method to each dataset in Red Datasets. You can get dataset as Numo::NArray's numeric subclass object.

This is a Ruby interface to STARCRAFT® II. Write your own AI using an easy interface and compete against others.