Normalizing Rows

The "Normalize" operator normalizes each numerical column (called an attribute in RapidMiner's terminology) within an example set to the desired range. Sometimes, you might want to normalize all the numerical values within a row (called an example within an example set in RapidMiner's terminology). I had to do this while understanding how term frequencies are calculated during document vector creation.

A nifty trick is to transpose the example set, normalize and then transpose it back again and the process here shows a very simple example.

This also shows the result of a document processing step which results in term frequencies for comparison. I recently found that RapidMiner performs a cosine normalization when producing term frequencies (it divides by the square root of the sum of the squares of the frequencies within a row which is equivalent to a document) and I wanted to see what differences show up when the sum of the frequencies is used instead (answer: not much with the data I was playing with).

Edit: added RapidMiner equivalent terminology for rows and columns

Counting words in a document

Here's an example that counts the total number of words in a document followed by the total number of unique words.

It does this by using the "cut document" operator with the following regular expression.

(\w+)

This splits the document into words and each word is returned as a document based on the result of the capturing group; the brackets define the capturing group; everything inside these is returned as a value. The "Documents To Data" operator converts all the documents, one for each word, into examples in an example set. The text field name is set to "word" and this is used in the later operators.

An "Extract Macro" operator obtains the number of examples. This is the same as the count of all words. An aggregation is performed to count words and another "Extract Macro" operator determines the number of unique words from the resulting example set. These macros are reported as log values using the "Provide Macro As Log Value" operators and the log file is converted to an example set using "Log To Data".

Other regular expressions could be used if you want to ignore numbers and inside the "Cut Document" operator it is possible to have other filtering operators such as stemming.

Generate Macro bonus features

I was pleased to discover that some of the functions available in the operator "Generate Attributes" are also available in the "Generate Macro" operator.

For example the following functions work.

concat
contains
matches
index
str
upper
lower
escape_html
replace

and I imagine that similar text processing functions will also work.

I tried date_now() and some other date functions and I got a result that looked like an error (actually quite an interesting error). So I assume date functions cannot be used.