Uploaded May 2026 | Updated September 2026, 2 weeks ago
Oracle Analytics Cloud data flows let you train a binary classifier, inspect model quality, and generate predictions from historical data without advanced coding. Use the same workflow to apply a saved model to new records, surface confidence scores, and analyze attrition risk in a workbook. Explore additional details and training at the resources linked below.
Train and apply a machine learning model in Oracle Analytics Cloud using data flows to turn historical records into practical predictions. The walkthrough shows how to prepare the source data, remove columns that do not contribute to the outcome, and configure a Train Binary Classifier step with the Naive Bayes algorithm for a yes or no prediction. It also shows how to set the target column, use the default training and testing split, save and run the model, inspect quality, and then apply the saved model to new records that contain the same input fields but not the outcome. After predictions are generated, the resulting data set includes a predicted value and confidence score, which can be reviewed in a workbook with a table and filter to highlight records at risk. The workflow provides a clear introduction to supervised machine learning in Oracle Analytics Cloud for teams that want to analyze employee attrition and act on predictions with more confidence.
00:00 Introduction to ML Models
00:24 Attrition Prediction Scenario
00:53 Create Data Flow
01:06 Configure the Binary Classification Model
01:48 Train Partition Percent Setting
02:20 Inspect the Machine Learning Model
02:40 Apply Trained Model
03:28 Generate and Save Prediction Results
03:51 Analyze Prediction Results in Workbook
Find training paths for Oracle Analytics and AI from beginner to advanced and expert: https://social.ora.cl/6000B8H6Ya
Explore self-paced short courses in the Oracle Analytics and AI Learning Hub: https://social.ora.cl/6002B8H6eq
Check out a detailed overview on data flows: https://social.ora.cl/6004B8H6s4
See how to view an Oracle machine learning model's detail information to help you understand the model and determine if it's suitable for predicting your data: https://social.ora.cl/6003B8H6v7
Like what you learned about Oracle Analytics Cloud? Subscribe now https://social.ora.cl/60025k87j
Join us at Oracle AI World: https://social.ora.cl/60035eVvJ
Contact AIDP sales: https://social.ora.cl/6003FLUMT
Learn more about Oracle AIDP: https://social.ora.cl/60047h76Q
Join the Oracle AIDP Community: https://social.ora.cl/60087h7Bj
Follow us here:
LinkedIn: https://social.ora.cl/60035eXuF
X: https://social.ora.cl/6008abVgG
Instagram: https://social.ora.cl/60095eXDN
Facebook: https://social.ora.cl/60065enQp
Oracle Analytics Cloud data flows let you train a binary classifier, inspect model quality, and generate predictions from historical data without advanced coding. Use the same workflow to apply a saved model to new records, surface confidence scores, and analyze attrition risk in a workbook. Explore additional details and training at the resources linked below.
Train and apply a machine learning model in Oracle Analytics Cloud using data flows to turn historical records into practical predictions. The walkthrough shows how to prepare the source data, remove columns that do not contribute to the outcome, and configure a Train Binary Classifier step with the Naive Bayes algorithm for a yes or no prediction. It also shows how to set the target column, use the default training and testing split, save and run the model, inspect quality, and then apply the saved model to new records that contain the same input fields but not the outcome. After predictions are generated, the resulting data set includes a predicted value and confidence score, which can be reviewed in a workbook with a table and filter to highlight records at risk. The workflow provides a clear introduction to supervised machine learning in Oracle Analytics Cloud for teams that want to analyze employee attrition and act on predictions with more confidence.
00:00 Introduction to ML Models
00:24 Attrition Prediction Scenario
00:53 Create Data Flow
01:06 Configure the Binary Classification Model
01:48 Train Partition Percent Setting
02:20 Inspect the Machine Learning Model
02:40 Apply Trained Model
03:28 Generate and Save Prediction Results
03:51 Analyze Prediction Results in Workbook
Find training paths for Oracle Analytics and AI from beginner to advanced and expert: https://social.ora.cl/6000B8H6Ya
Explore self-paced short courses in the Oracle Analytics and AI Learning Hub: https://social.ora.cl/6002B8H6eq
Check out a detailed overview on data flows: https://social.ora.cl/6004B8H6s4
See how to view an Oracle machine learning model's detail information to help you understand the model and determine if it's suitable for predicting your data: https://social.ora.cl/6003B8H6v7
Like what you learned about Oracle Analytics Cloud? Subscribe now https://social.ora.cl/60025k87j
Join us at Oracle AI World: https://social.ora.cl/60035eVvJ
Contact AIDP sales: https://social.ora.cl/6003FLUMT
Learn more about Oracle AIDP: https://social.ora.cl/60047h76Q
Join the Oracle AIDP Community: https://social.ora.cl/60087h7Bj
Follow us here:
LinkedIn: https://social.ora.cl/60035eXuF
X: https://social.ora.cl/6008abVgG
Instagram: https://social.ora.cl/60095eXDN
Facebook: https://social.ora.cl/60065enQp
