# 7.00.02 - TF_IDF Arguments - Aster Analytics

## Teradata Aster® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Release Date
September 2017
Content Type
Programming Reference
User Guide
Publication ID
B700-1022-700K
Language
English (United States)
Formula
[Optional] Specifies the formula for calculating the term frequency (tf) of term t in document d:
• 'normal' (normalized frequency, default)

tf(t,d) = f ((t,d) / sum {w,wd}

This value is rf divided by the number of terms in the document.

• 'bool' (Boolean frequency)

tf((t,d) = 1 if t occurs in d; otherwise, tf((t,d) = 0.

• 'log' (logarithmically-scaled frequency)

tf((t,d) = log(f((t,d)+1)

where f((t,d) is the number of times t occurs in d (that is, the raw frequency, rf).

• 'augment' (augmented frequency, which prevents bias towards longer documents)

tf((t,d) = 0.5 +

(0.5 × f ((t,d) / max {f(w,d) : wd })

This value is rf divided by the maximum raw frequency of any term in the document.

When using the output of a previous run of the TF_IDF function on a training document set to predict TF_IDF scores on an input document set, use the same Formula value for the input document set that you used for the training document set.