Sold by: H2O.ai
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
Sold by
Categories
Delivery method
Latest version
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Features and programs
Trust Center
Access real-time vendor security and compliance information through their Trust Center powered by Drata or Vanta. Review certifications and security standards before purchase.
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
This product is available free of charge. Free subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimensions summary
This algorithm is free to license, so you pay only for the AWS compute hours you use. Pricing splits into three activities: training the model, batch inference, and real-time inference. Within each activity, you pick an instance type from two families, the compute-optimized c4 and c5 lines and the general-purpose m4 and m5 lines. Billing is per host hour (HostHrs). Cost scales with the instance size you choose, since larger instances offer more processing power. You match the mode and instance size to your workload and control spend by selecting accordingly.
Top-of-mind questions for buyers
One host hour is one running instance for one hour of the chosen mode. Each instance you launch meters its own hours. Running two instances for one hour counts as two host hours. Larger instance types cost more per hour because they provide more processing capacity.
Both meter per host hour on the instance type you pick. Batch mode runs inference on a dataset and stops, so you pay only for that job's runtime. Real-time mode keeps an endpoint running to serve live requests, so hours accrue for as long as the endpoint stays up.
Host hours accrue while the instance runs, not by request volume. A real-time endpoint keeps billing hours even when idle until you shut it down. A finished or stopped training or batch job stops accruing software charges once the instance is no longer running.
www.h2o.ai
Helpful?
Vendor refund policy
There is no refund policy as this algorithm is offered for free
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
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
Resources
Vendor resources
Support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Similar products
A multi-layer feedforward artificial neural network
H2O Driverless AI brings Automatic Machine Learning for the enterprise.
Implementation of H2O.ai's AutoML Algorithm from H2O-3 Library
H2O.ai provides complete AI convergence across Predictive AI, Generative AI, and Agentic AI, offering a comprehensive AI tech stack that empowers you to build and secure your own AI workflows and solutions.
Our end-to-end SaaS AI platform is a fully managed cloud-native solution, delivering seamless scalability, robust security, and enterprise-grade performance. With H2O AI Cloud, you own every part of your AI stack - your data, your prompts, and your models - ensuring full control, privacy, and security over your AI initiatives.
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.