Statistical Methods with Domain-based Models
Blog: Decision Management Community
Machine learning is a statistical modeling technique, which finds and correlates patterns between inputs and outputs without necessarily capturing their cause-and-effect relationships. Data derived from human behavior is dynamic and ever-changing. Such messy data is difficult to analyze to make predictions. This WSJ article gives examples when ML-based solutions have been enhanced by the inclusion of pre-defined domain-specific models. Link Advantages and the integrated models:
- they can be trained or customized with much smaller data sets
- they can tolerate much more noise in the data
- they can be continually updated with new data reflecting changing conditions
- it’s easier to explain how a decision or recommendation was arrived at
- such augmented AI solutions help capture cause-and-effect relationships.
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