Cross Validation

#Terms

WHAT IS… ?

Cross-validation is a statistical method used to estimate the performance of a model on unseen data.  It’s best for situations where there is not much training data available.

     

    HOW IS IT USED ?

    Obtain realistic estimates of the performance of a model. Cross Validation is a powerful tool used in data science as a way to estimate the performance of machine learning and deep learning algorithms on unseen data. It is used to asses the performance of models before their deployment in production.

    Empower your data science team and make the most of

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    $ pip install shapelets-soloCopy to clipboard

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    Learn more by reading our installation guide and tutorials.

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    FAQS / Any question?

    Is there any current solution on the market that is as efficient as Shapelets?

    There are fantastic tools out there, no doubt! But these tools are not integrated with your analytical workflows, security systems, web apps infrastructure, etc. When working with Shapelets, you'll get that feeling of self-integration. A platform where you can run all your workflows efficiently.

    What is the licensing model for Shapelets?

    The license model is very simple. Shapelets comes as a built-in box, it is based on the amount of resources you are powering in the platform. It is not based on the number of users, or the volume of data you put into the system.

    Regarding data visualization, can I share my project with third parties?

    Yes, you can share your project with third parties. Additionally, you can create different users and edit the permissions for your team to edit, create or share a project.

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