Outliers in a big dataset
Hello, i'm a total newby with Rapidminer.
I have a big dataset with targets with numeric values and many (34) attributes.
I have to estimate the value of the target value and i will use a linear regression.
Now I want to detect outliers but RM freezes whenever I do this.
What is the best way to tackle this? Do I need to downsize the dataset with the Sample operator?
Or should should i use the "Remove useless attributes" operator and maby also downsize the dataset?