Across
- 3. Detecting irregular pattern
- 4. Unusual data point
- 5. Stepwise visual change
- 7. User group over time
- 9. Grouping similar data
- 10. Data structure layout
- 11. Delay in data trend
- 12. Predicting customer exit
- 17. Customer grouping metric
- 18. Predicting future trends
- 19. Many models combined
- 20. Unified data storage
- 21. Data pattern discovery
- 22. Splitting text units
- 23. Collinearity detector
- 24. Product feature tradeoff
- 26. Filling missing values
- 28. Likelihood to act
Down
- 1. Change in data behavior
- 2. Random simulation method
- 6. Model performance booster
- 7. Cause and effect link
- 8. Dividing customers smartly
- 9. Relationship strength measure
- 13. Scaling data evenly
- 14. Selecting data subset
- 15. Finding item associations
- 16. Estimating relationships
- 25. Visual summary panel
- 27. Color data pattern
- 28. Cutting model branches