kNear
kNear is a JavaScript library that implements the k-nearest neighbors algorithm for supervised learning. It classifies new numeric data points based on their proximity to previously learned classifications, making it an effective tool for various machine learning applications. Users can seamlessly integrate it into their projects using npm.
Top kNear Alternatives
Feature Forge
Feature Forge offers a robust toolkit for crafting and validating machine learning features, seamlessly integrating with scikit-learn.
KRFuzzyCMeans-Algorithm
KRFuzzyCMeans implements the Fuzzy C-Means algorithm for clustering and classification within machine learning.
BIDMach
BIDMach is a high-performance machine learning library designed for both CPU and GPU acceleration.
ml.js
ml.js offers a collection of specialized machine learning tools tailored for JavaScript, primarily designed for browser use.
AIToolbox
AIToolbox offers a suite of AI modules in Swift, including Support Vector Machines, Neural Networks, and Genetic Algorithms, optimized with the Accelerate library for enhanced performance.
Spearmint
Spearmint is a robust software package that facilitates Bayesian optimization by automating experimental processes.
Topik
Its high-level interface simplifies exploratory analysis of text datasets, featuring an easy callable function and...
SwiftLearner
It features straightforward algorithms using plain Java types with minimal dependencies, ideal for prototyping and...
SuperLearner
It integrates user feedback for continuous improvement and provides extensive resources, including vignettes and academic...
SimpleAI
Designed with a modern Pythonic approach, it emphasizes stability and maintainability, providing clear documentation and...
Vulpes
Designed for Visual Studio, it efficiently processes the MNIST handwritten digit dataset through pretraining and...
LDA.js
It skillfully identifies multiple topics within documents, extracting relevant keywords while filtering out common terms...
KRHebbian-Algorithm
Version 1.3.0 is designed to efficiently process feedback, allowing users to refine inputs for optimal...
Top kNear Features
- Efficient proximity classification
- Simple JavaScript integration
- Open-source MIT License
- User-friendly documentation
- Real-time learning capability
- Supports numeric data points
- Flexible for diverse applications
- Lightweight and fast performance
- Customizable algorithm parameters
- Active community support
- Easy installation via npm
- Cross-platform compatibility
- Continuous feedback incorporation
- Scalable for large datasets
- Visual representation of results
- Intuitive API design
- Adaptive to changing data
- Robust error handling features
- Well-defined training process
- Comprehensive example projects.
