Fregata

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Fregata is an open-source machine learning library built on Apache Spark, offering high-level APIs in Scala. It provides super-fast, large-scale machine learning algorithms for classification, regression, and clustering.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is Fregata?

Fregata is a lightweight, super-fast, and large-scale machine learning library designed for Apache Spark. It offers high-level APIs in Scala, enabling developers and data scientists to build and deploy intelligent applications efficiently. A key differentiator is its ability to achieve higher accuracy and significantly faster convergence compared to MLLib, often training Generalized Linear Models in minutes for massive datasets. Fregata utilizes GSA SGD optimization, making it parameter-free by dynamically calculating appropriate learning rates. It supports Spark 1.x and 2.x with Scala 2.10 and 2.11, and includes algorithms like Trillion LR, Trillion SoftMax, and Logistic Regression. Its architecture is designed for seamless integration into existing Spark data processing workflows.

Best used for

Ideal for data scientists and developers who need to build and deploy high-performance machine learning models on Apache Spark, process large-scale datasets efficiently, and implement advanced classification or regression algorithms. Especially valuable for those seeking faster convergence and parameter-free optimization in their ML workflows.

Common actions

build machine learning models

process large datasets

implement classification algorithms

integrate with Apache Spark

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Capabilities

Key features

Large-scale machine learning
High-level Scala APIs
Super-fast convergence
Parameter-free optimization
Spark 1.x/2.x compatibility
Classification, Regression, Clustering

Target Audience

developerdata scientist

Integrations

apache-spark

Pricing & Plans

Open Source

Free

FAQs

What kind of machine learning algorithms does Fregata support?

Fregata primarily supports classification algorithms such as Trillion LR, Trillion SoftMax, and Logistic Regression. While regression and clustering functionalities are mentioned, they are noted as 'will release later' in the documentation, indicating ongoing development or future plans.

How does Fregata achieve faster performance compared to MLLib?

Fregata achieves faster performance through its GSA SGD optimization, which allows for rapid convergence, often in a single data epoch for Generalized Linear Models. It also dynamically calculates appropriate learning rates, eliminating the need for manual tuning and improving efficiency.

What are the system requirements for using Fregata?

Fregata is built on Apache Spark and supports Spark versions 1.x and 2.x. It requires Scala versions 2.10 or 2.11 for its high-level APIs. Users can integrate it into their projects via Maven or SBT by adding the specified dependencies.

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