Join Barton Poulson for an in-depth discussion in this video Anomaly detection in RapidMiner, part of Data Science Foundations: Data Mining.
- [Instructor] The first thing I need…to do is import the process.…I'll come up to File…to Import Process.…I've got it on my Desktop.…There it is right there.…So that's imported.…It's not saved however,…so I'm gonna come up…and save it and put it…into my repository.…Save Process As.…I'll type in the same name…I had on the Desktop…and tell it to put it…into my processes here.…Click OK.…There it is saved now.…
That's good.…I also need to import the data.…So I'll go to Add Data.…It's on my computer…on the Desktop again.…It's AnomalyData.csv.…So I'll click on that…and I'll go to Next.…Here it asks me how to read the data.…This part's fine.…We get to format your columns.…I'm going to make a couple…of changes here.…Now most of the variables here…are real, so they're just numeric.…We have a polynomial here,…which means several different…categories for a state code.…At the end here,…we also have PsychRegion,…region, and division.…
Those are also polynomials.…So I just have to set those…to be polynomial.…And then division's also polynomial.…
Barton Poulson covers data sources and types, the languages and software used in data mining (including R and Python), and specific task-based lessons that help you practice the most common data-mining techniques: text mining, data clustering, association analysis, and more. This course is an absolute necessity for those interested in joining the data science workforce, and for those who need to obtain more experience in data mining.
- Prerequisites for data mining
- Data mining using R, Python, Orange, and RapidMiner
- Data reduction
- Data clustering
- Anomaly detection
- Association analysis
- Regression analysis
- Sequence mining
- Text mining
Skill Level Beginner
Transitioning from Data Warehousing to Big Datawith Alan Simon1h 50m Intermediate
Manage Your Organization's Big Data Programwith Alan Simon1h 11m Intermediate
2. Data Reduction
5. Anomaly Detection
6. Association Analysis
7. Regression Analysis
8. Sequential Patterns
9. Text Mining
Next steps1m 18s
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