ML Models in Fire Insights
Fire enables you to create ML models. Fire supports ML models using Spark ML, H2O, Scikit Learn, AWS SageMaker and Tensorflow.
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.
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.
Fire Insights not only enables you to create your ML Models, but it also enables you to do a detailed analysis of them.