Logistic regressor using Normally distributed variables
Roav RAN is a modular JavaScript-based framework for running RAN . The application begins at `src/experiment/index.js`, which manages and calls the various views that control different aspects of the test.
Roav MEP is a modular JavaScript-based framework for running MEP . The application begins at `src/experiment/index.js`, which manages and calls the various views that control different aspects of the test.
Run CNN and MLP machine learning models for regression and classification tasks in your smartphone
Random Forest from scratch in C11, compiled to WebAssembly -- classification, regression, ExtraTrees, quantile RF, conformal prediction, histogram binning, JARF rotation, sample weights, proximity matrix
React data grid for beautifully displaying and editing large amounts of data with amazing performance.
Turn any webpage into structured data using LLMs (OpenAI compatible APIs)
Declarative Specifications of Visual Analytics Processes
Vowpal Wabbit Node.js Stream
neurova AI ML — classical learners with .train()/.infer() (port of Python nalyst).
Popular algorithms of machine learning are made available
Derivatives and multiples pricing for racing and sports.
Time series forecasting library
Fast Random Forest library.
A professional Rust implementation of the Tsetlin Machine algorithm
Random forest regressor and classifier
Regress out unwanted per-cell covariates from a single-cell count matrix via per-gene OLS — matches scanpy pp.regress_out (residuals of expression on intercept+covariates)
dependancy free, machine learning
Linear models for the ferrolearn ML framework
Python bindings for ferrolearn via PyO3
Neural forecasting models implemented using ruv-FANN for time series forecasting
ScAlaBle Estimator Regressor for heritability estimation
Package for algorithms related to K Nearest Neighbors
Regressor generates regression specs based on ActiveRecord models. Currently relations, validations, attributes, and database indexes are supported.
Gem to build simple regressors and classifiers into your application, without necessarily having to understand all the math behind.
Shoulda Matchmakers generates regression specs for existing ActiveRecord models and ActionController controllers using Shoulda Matchers. It generates specs for model validations, associations, nested attributes, enum definitions, attribute serialization, database columns and database indexes as well as controller REST routes, and before/after/around actions/filters. It can also generate FactoryGirl factories containing the minimum attributes required for the factory to create a valid object. Shoulda Matchmakers is based on the Regressor gem by Erwin Schens.