Data preparation
Includes interactive data preparation tools that make it easy to apply required data transformations, derive new variables and run intelligent feature selection methods, such as variable selection based on trees and random forests.
Enabling modelers and statisticians to work more efficiently, so they have more time to unearth valuable insights buried in granular segments to reveal new opportunities, expose hidden risks and fuel smarter, well-timed decisions.
Customizable model templates
Provides out-of-the-box model building templates that can be customized and shared across projects and users.
Self-service machine learning techniques
Includes linear regression, logistic regression, decision trees, random forests, generalized linear models, gradient boosting, neural networks, Bayesian network and support vector machines.
Champion model identification
Uses a variety of interactive, customizable assessment techniques to automatically select the champion model for each segment.
Model exception identification
Provides standardized, easy-to-understand reports that pinpoint issues with models and identify the best models with high confidence. You can then easily recognize underperforming models.
Model retraining
Lets you retrain models over time using new data and variables, including REST endpoints.
Scalable processing
Runs analytical procedures on a single machine, via grid computing or in-memory processing.
Flexible model deployment
Lets you deploy models in database or in Hadoop to score new data using SAS Scoring Accelerator.
Add-on to SAS® Enterprise Miner™
SAS Factory Miner runs as an add-on to SAS Enterprise Miner.
Build and retrain hundreds of predictive models across multiple segments – quickly and easily. Then automatically pick the best model for each segment.
Boost model building productivity.
Reap huge productivity gains by automating time-consuming model development processes – including data prep, variable transformation, predictor variable, algorithm selection, etc. SAS Factory Miner has an easy-to-use, web-based interface that lets you build multiple models for each segment, and automatically identify the most accurate one.
Automate model development.
Choose the best segmentation strategy to solve your business problems. And jump-start your predictive modeling with prebuilt model building templates that you can customize to fit your needs. Automated reporting and documentation make it easy to share best practices on model design and results across your organization.
Explore new ideas faster.
Apply machine learning and predictive analytics techniques to large, complex data sets, and get the results fast. If a model fails, you can try again quickly using different inputs or ideas. As variables change or new variables are found, you can test them without having to rebuild the entire data mining flow or challenge an existing set of algorithms.
Put models into operation quickly.
Deploy champion models in different production environments with just the click of a button. SAS Factory Miner automatically generates complete scoring code – including all necessary data prep and transformation steps. And retraining models is easy because all assets related to model development and deployment are centrally managed and accessible via REST endpoints.
Explore More on SAS® Factory Miner and Beyond
WHITE PAPER
Learn how the SAS Analytics Life Cycle can guide you through the iterative process of going from raw data to predictive modeling to automated decisions, faster.
REPORT
Learn why Gartner named SAS a Leader in the Magic Quadrant for Data Science Platforms.
INSIGHTS
Get the lastest news, views and insights on analytics from the brightest minds in the business.
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