naive solver for the prime factorization problem
Cholesky Factorization of ndarrays
A JavaScript library for efficient immutable updates
A Vue 3 Component Library. Fairly Complete, Theme Customizable, Uses TypeScript, Fast
Tests whether one path is inside another path
C++ bindings for all single- and double-precision CLAPACK (Linear Algebra Package) routines.
Detect whether the terminal supports Unicode
The official nuxt module for naive-ui that supports Nuxt.js SSR.
This is the source for tooling for naively turning documents and rich text fields into HTML, deserializing them, combining them with source documents, and patching them back. Ideally, this should take in objects that are in portable text, text arrays, or
Forked from Naive UI. A Vue 3 Component Library. Fairly Complete, Theme Customizable, Uses TypeScript, Fast
A renderless Vue.js cron editor.
Unofficial Naive UI module for Nuxt
Naive code printer for bracket languages
Naive Bayes Text Classifier
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lightweight vue.js cron editor
No description provided.
CSP-style channel library using ES7 async/await keywords
Selectors decision tree - choose matching selectors, fast
A Vue 3 business component library built on Naive UI.
tiny modular DOM lib for ie9+
@form-create/naive 内置组件
@form-create/naive-ui 内置组件
@form-create/naive-ui 内置组件
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.
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.