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Naive Bayesian Classification for Golang

Naive Bayesian Classification for Golang that perform classification into an arbitrary number of classes on sets of strings.

Best Naive Bayesian Classification for Golang Alternatives & Competitors

The best Naive Bayesian Classification for Golang alternatives based on verified products, community votes, reviews and other factors.
Filter: 8 Open-Source Alternatives.

  1. Exploratory enables users to understand data by transforming, visualizing, and applying advanced statistics and machine learning algorithms.

    Key Exploratory features:

    User-friendly Interface Integration with R Rich Visualization Options Collaborative Features

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  2. scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

    Key Scikit-learn features:

    Ease of Use Extensive Documentation and Community Support Integration with Other Libraries Variety of Algorithms

    Open Source

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  4. WEKA is a set of powerful data mining tools that run on Java.

    Key WEKA features:

    User-Friendly Interface Wide Range of Algorithms Open Source Extensive Documentation

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  5. Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.

    Key Dataiku features:

    User-Friendly Interface Collaborative Environment End-to-End Workflow Integrations and Extensibility

    /dataiku-alternatives
  6. OpenCV is the world's biggest computer vision library.

    Key OpenCV features:

    Comprehensive Library Cross-Platform Compatibility Open Source Large Community Support

    Open Source

    /opencv-alternatives
  7. Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

    Key Pandas features:

    Data Wrangling Flexible Data Structures Integration with Other Libraries Performance with Data Size

    Open Source

    /pandas-alternatives
  8. GraphLab Create is an extensible machine learning framework that enables developers and data scientists to easily build and deploy apps.

    Key Turi GraphLab Create features:

    Ease of Use Scalability Integrated Toolset Graph Processing Capabilities

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  9. NumPy is the fundamental package for scientific computing with Python.

    Key NumPy features:

    Performance Versatility Ease of Use Community Support

    Open Source

    /numpy-alternatives
  10. htm.java is a Hierarchical Temporal Memory implementation in Java, it provide a Java version of NuPIC that has a 1-to-1 correspondence to all systems, functionality and tests provided by Numenta's open source implementation.

    Key htm.java features:

    Biologically Inspired Algorithms Time Series Prediction Open Source Java Ecosystem Integration

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  11. Figure Eight is the essential Human-in-the-Loop Machine Learning platform.

    Key Figure Eight features:

    Scalability Diverse Workforce Workflow Customization Integration Capabilities

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  12. The DimML programming language enables users to run any data solution on any website with only a single line of code.

    Key DimML features:

    Ease of Use Scalability Integration Customization

    /dimml-alternatives
  13. Logical Glue helps Lenders and Insurance organisations make better decisions with a highly intuitive and user-friendly Machine Learning Platform.

    Key Logical Glue features:

    Interpretability User-Friendly Interface Automated Machine Learning Regulatory Compliance

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  14. RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

    Key RapidMiner features:

    Ease of Use Integration Capabilities Comprehensive Feature Set Community and Support

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