regression-js vs mathjs

Side-by-side — pricing, strengths, tradeoffs, and fit.

regression-js

JavaScript library for least squares fitting methods.

mathjs

An extensive math library for JavaScript and Node.js with support for symbolic computation.

At a glance

Open SourceFree Tier
◌ Declining·From $0
Open SourceFree Tier
● Established·From $0

Overview

One-liner

JavaScript library for least squares fitting methods.

One-liner

An extensive math library for JavaScript and Node.js with support for symbolic computation.

Maturity

Declining

Maturity

Established

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Open source — free to use

Starts at

$0

Starts at

$0

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Web developers needing to integrate statistical models into their projects.
Data analysts working with JavaScript who require least squares fitting methods.

✓ Best for

Web developers who need to perform complex mathematical operations in their JavaScript applications.
Educational software developers requiring a robust math library with symbolic computation support.
Data analysts working on projects that require advanced numerical and symbolic processing.

Not ideal for

✕ Not for

Projects requiring real-time data processing and analysis beyond the capabilities of a library.
Users looking for a full-service analytics platform rather than a specialized library.

✕ Not for

Projects needing real-time, high-performance numerical computations where speed is critical.
Applications that require heavy integration with specific frameworks not supported by MathJS.

Strengths

↑ Strengths

Various least squares fitting methods for data analysis.
Easy integration into web applications and Node.js projects.
Comprehensive documentation and examples.

↑ Strengths

Support for symbolic computation and numerical operations.
Extensive mathematical functions including trigonometry, logarithms, and complex numbers.
Flexible expression parser with support for custom operators and functions.
Integration with JavaScript's native Math library.

Weaknesses

↓ Weaknesses

Limited support for advanced statistical methods
Performance issues with large datasets
Small community and limited third-party contributions

↓ Weaknesses

Limited performance for heavy numerical computations compared to specialized libraries like NumPy
Documentation lacks depth in explaining advanced features
Community and support are relatively smaller compared to more established libraries
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