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Topic: Data Cleansing You want to detect outliers on a data set of 500 examples and 4 regular numeric attributes with different ranges. You are
Topic: Data Cleansing You want to detect outliers on a data set of 500 examples and 4 regular numeric attributes with different ranges. You are unsure if these attributes are truly independent of one another so you must assume they are not. In this case you should (Select ANY correct answer) A. normalize the data first, and then use an outlier detection operator. B. use an outlier detection operator first, then normalize the data. C. use HBOS as it allows for attribute dependencies. D. use Local Outlier Factor as it allows for attribute dependencies
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