Reading and writing xlsx files in RapidMiner

The other day, I stumbled on a nifty way to import and export xlsx files into and out of RapidMiner.

There's an R package called "xlsx" that is able to read and write Excel files including Excel 2007 xlsx format. 

Here's a process that loads the iris data, writes this to an xlsx file at c:\temp\iris.xlsx and then reads it back again.

(Note: after the first run, comment out the line in the R script that installs the xlsx package to avoid downloading the R package again)

Edit: 12/7/12: The new version of RapidMiner supports this - hurrah!

Deleting attributes with a single valid value

Removing attributes where one or more of the examples are missing is easy using the "Select Attributes" operator with the option "no missing values".

If however, you want to additionally remove attributes where only a single example is valid and all the rest are missing, a neat way to do this is to use the "Remove Useless Attributes" operator. One of the parameters to this is "numerical min deviation" and this will remove any attribute with a deviation less than or equal to the value supplied which defaults to 0. Attributes with only a single valid value will have a deviation of 0 and will therefore be removed by this operator.

Operators that deserve to be better known: part III

Normalize

Of course this is already a well known operator but it has a useful option I discovered the other day. If you set the method to "proportion transformation", the normalization divides each numerical attribute with the sum of all the values for that attribute. This has the effect that the sum of each normalized attribute becomes 1.

This is much easier than using loop operators which would involve having a "loop examples" operator inside "loop attributes" with filtering, calculating sums, generating attributes and perhaps some attribute selection.