Results for ml-random-forest

Random forest for classification and regression

Choose randomly from a selection of elements

JavaScript implementation of the XORSHIFT-ADD (XSadd) pseudo random number generator

Random forest for classification and regression

NodeJS implementation of decision tree, random forest, and XGBoost algorithms with comprehensive performance testing (Node.js 20+)

Matrix manipulation and computation library

Get the maximum value in an array

Various method to process spectra

Get the minimum value in an array

Compute the euclidean distance between two vectors

Random forest for classification and regression

Rescale an array into a range

Generates markdown API documentation from jsdoc annotated source code

Official Express/Sequelize Liana for Forest

High-performance (binary) tree and sorted map implementation (AVL, Splay, Radix, Red-Black)

Web Assembly streaming Opus decoder with Machine Learning enhancements

Node.js runfiles helpers for Bazel

Official package for all Forest Express Lianas

Auditable & minimal JS implementation of post-quantum cryptography: FIPS 203, 204, 205, Falcon

Find anomalies in a set of data using the isolation forest algorithm

Find the nearest point to a sample point

Generate fallback values for content with alt text

Get the average value in an array

Generate random numbers from various distributions.

This Ruby gem leverages Machine Learning(ML) techniques to make predictions(forecasts) and classifications in various applications. It provides capabilities such as predicting next month's billing, forecasting upcoming sales orders, identifying patient's potential findings(like Diabetes), determining user approval status, classifying text, generating similarity scores, and making recommendations. It uses Python3 under the hood, powered by popular machine learning techniques including NLP(Natural Language Processing), Decision Tree, K-Nearest Neighbors and Logistic Regression, Random Forest and Linear Regression algorithms.