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Models in Sparkflows

ML Models in Fire Insights


Overview

Fire enables you to create ML models. Fire supports ML models using Spark ML, H2O, Scikit Learn, AWS SageMaker and Tensorflow.


Model Creation


Fire provides a number of processors for creating ML models for Regression, Classification and Clustering. These can be created using the Spark ML, H2O, AWS Sagemaker, Scikit Learn and Tensorflow processors.


Summary of the ML Models created


Fire provides a Summary view of the ML models created.


ML Models List


Fire provides a rich view for the various ML Models created in Fire Insights. Below screenshot shows a listing of ML models which have been built.




ML Model Details


Fire provides a detailed view of the various ML Models.

Below is a view of the Model Summary.




Below is a view of the Features Importance.




Below shows the list of Features which were used in building the ML Model.



Model Comparison


Fire Insights enables you to also compare the various ML models created. For example, if multiple models were created over time for a specific problem, the various models can be easily compared.


Summary


Fire Insights not only enables you to create your ML Models, but it also enables you to do a detailed analysis of them.


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