Project credit card fraud detection, where do I go from here?
Contributor II
This is the data set, 3,000 rows with 31 columns.
This is the template used for outlier detection:
This is my process:
I don't understand how Apply Model or Filter Examples work here. If
anyone knows, please let me know. I'm a newbie to RapidMiner, which is
why the template is invaluable. Originally my data set had more than
285,000 rows. Detect Outlier took forever to run. I cut the data set down to
3,000 rows, the program ran in two minutes.
This is the Output:
As promised in the template there is clustered data, two example sets, one
outlier, one non-outlier. Cluster_1 has the outlier distance 5.953. This is
probably an anomaly.
What do I need to do next to complete this project?
Tony
This is the template used for outlier detection:
This is my process:
I don't understand how Apply Model or Filter Examples work here. If
anyone knows, please let me know. I'm a newbie to RapidMiner, which is
why the template is invaluable. Originally my data set had more than
285,000 rows. Detect Outlier took forever to run. I cut the data set down to
3,000 rows, the program ran in two minutes.
This is the Output:
As promised in the template there is clustered data, two example sets, one
outlier, one non-outlier. Cluster_1 has the outlier distance 5.953. This is
probably an anomaly.
What do I need to do next to complete this project?
Tony
0
Best Answer
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Telcontar120
Moderator, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,635 
Unicorn
@tonyboy9 I think you have several parallel threads on this topic now open. You might consider marking some of them resolved so you can consolidate your ongoing issues in one place. I am having a hard time knowing which of these is current and which is outdated.5
