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Deployed on AWS
GLM Algorithm - From H2O-3 Library
Overview
Generalized Linear Models (GLM) estimate regression models for outcomes following exponential distributions. In addition to the Gaussian (i.e. normal) distribution, these include Poisson, binomial, and gamma distributions. Each serves a different purpose, and depending on distribution and link function choice, can be used either for prediction or classification.
Highlights
- Generalized linear model, by H2O.ai from H2O-3 library
Details
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Latest version
Deployed on AWS
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Delivery details
Amazon SageMaker algorithm
An Amazon SageMaker algorithm is a machine learning model that requires your training data to make predictions. Use the included training algorithm to generate your unique model artifact. Then deploy the model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Initial release of H2O.ai H2O-3 GLM algorithm for SageMaker
Additional details
Inputs
- Summary
See http://docs.h2o.ai/h2o/latest-stable/h2o-py/docs/modeling.html#h2ogeneralizedlinearestimator for all hyperparameter definitions. NOTE: Required hyperparameter is "training", make sure to specify "family" for prediction as some distributions require categorical values. The data ingest process does not automatically encode categorical values
- Input MIME type
- csv, text/csv, s3
See Input Summary
See Input Summary
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Vendor resources
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