Lasso.js is a build tool and runtime library for building and bundling all of the resources needed by a web application
Lasso selection plugin for Leaflet
Lasso (least absolute shrinkage and selection operator) Regression
A taglib to use Marko with Lasso
A responsive react tool for marking irregular areas in images (lasso / free select)
Lasso selection plugin for Cytoscape
TypeScript definitions for lasso
Use lasso selection tool
karma plugin for lasso
Core runtime and reusable package for Service Lasso.
A d3 plugin for lasso selecting elements
Lasso and Marko extras
Lasso Tools
Lasso is a local-first workflow compiler for pi-duroxide.
gulp plugin for lasso
lasso select helper
personal lasso configuration
Lasso.js plugin to support compilation of Marko templates
High-performance WebGL scatterplot component for React with pan/zoom and lasso selection
Lasso.js plugin to support Node.js style module require in the browser
Desktop-like drag & drop for Nuxt - Lasso selection, grid layout, drop zones, fully customizable
Get image info (URL, width and height) on both the server and the client
Lasso.js transform that uses Babel to transpile ES6 code to ES5.
A taglib to use Marko with Lasso
A multithreaded and single threaded string interner that allows strings to be cached with a minimal memory footprint, associating them with a unique key that can be used to retrieve them at any time.
Lightweight regression library (OLS, Ridge, Lasso, Elastic Net, WLS, LOESS, Polynomial) with 14 diagnostic tests, cross validation, and prediction intervals. Pure Rust - no external math dependencies. WASM, Python, FFI, and Excel XLL bindings.
String interning for Gentoo-related crates
A pure-Rust library for modeling working capital drivers using Finite Impulse Response (FIR) filters, with support for manual profiles and automatic lag selection via OLS and Lasso
Spatial gene regulatory network inference and in-silico perturbation (Rust port of SpaceTravLR)
Spatial gene regulatory network inference and in-silico perturbation (Rust port of SpaceTravLR)
Linear models for sklears: linear regression, logistic regression, and GLMs
Linear models for the ferrolearn ML framework
Covariance estimation algorithms
Fast memory-efficient solver for sparse generalized linear models
Machine Learning algorithms that are based on regression techniques
Core library for the srsadmm project, used to solve consensus ADMM problems with serverless compute.
Identity herding with OAuth
Rumale::LinearModel provides linear model algorithms, such as Logistic Regression, Support Vector Machine, Lasso, and Ridge Regression with Rumale interface.
Lasso for Methods! You can hook up processes before and after to existing method objects, it's like a monkey patch without have to open up the actually method.
Rumale is a machine learning library in Ruby. Rumale provides machine learning algorithms with interfaces similar to Scikit-Learn in Python. Rumale supports Support Vector Machine, Logistic Regression, Ridge, Lasso, Multi-layer Perceptron, Naive Bayes, Decision Tree, Gradient Tree Boosting, Random Forest, K-Means, Gaussian Mixture Model, DBSCAN, Spectral Clustering, Mutidimensional Scaling, t-SNE, Fisher Discriminant Analysis, Neighbourhood Component Analysis, Principal Component Analysis, Non-negative Matrix Factorization, and many other algorithms.
SVMKit is a machine learninig library in Ruby. SVMKit provides machine learning algorithms with interfaces similar to Scikit-Learn in Python. SVMKit supports Linear / Kernel Support Vector Machine, Logistic Regression, Linear Regression, Ridge, Lasso, Factorization Machine, Naive Bayes, Decision Tree, AdaBoost, Random Forest, K-nearest neighbor algorithm, K-Means, DBSCAN, Principal Component Analysis, and Non-negative Matrix Factorization. Note that the SVMKit has been deprecated and has been renamed to Rumale.
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