This code pattern strolls you through how to anticipate deceitful deals utilizing historic information and demonstrates the automatic process of structure models utilizing the Findability Platform Predict Plus operator from Red Hat Market.
- Red Hat Market: An easier method to buy and handle enterprise software, with automated implementation to any cloud
- Findability Platform Predict Plus: An automated, self learning, and multi-modeling AI tool that manages discrete target variables, continuous target variables, and time series data with no need for coding
- Red Hat OpenShift Container Platform: A hybrid cloud, enterprise container platform that empowers designers to innovate and ship faster
After completing this code pattern, you will comprehend how to:
- Quickly set up the circumstances on an OpenShift cluster for model structure.
- Ingest the information and initiate the FP Predict Plus procedure.
- Construct various designs utilizing FP Predict Plus and examine the efficiency of those models.
- Choose the best design and finish the implementation.
- Produce brand-new forecasts utilizing the released model.
- User logs into the FP Predict Plus platform using a circumstances of the FP Predict Plus Operator.
- User publishes the data file in the CSV format to the Kubernetes storage on the Red Hat OpenShift platform.
- User starts the model-building process using the FP Predict Plus operator on an OpenShift cluster and produces pipelines.
- User assesses various pipelines from FP Predict Plus and picks the very best model for release.
- User produces accurate predictions by utilizing the deployed design.
Find the in-depth steps for this pattern in the README file. The steps will reveal you how to:
- Include the data
- Produce a task
- Evaluation the task details
- Evaluate results
- Download the model file
- Make forecasts utilizing new data
- Develop a predict task
- Check job summary
- Analyze outcomes of forecast job
- Download the forecasted outcomes
View the detailed actions