Memory-based learning: Predicting gender of French nouns I'm trying to predict the gender of French nouns based on their suffixes. I have a corpus of 10k nouns. For each noun, I split the root from the suffix. I create five instances but with varying suffix lengths: 1, 2, 3, 4 and 5.
The class name I'm assigning to each instance is composed of the gender and the length of the suffix, e.g. "f2" for a feminine noun with a suffix of the length 2.
To give you an idea of how the data looks, here's a small extract:
http://pastebin.com/tn6DFJAy
Do you think this is a reasonable approach? Is it sensible to separate the classes based on the suffix length? And is it safe to generate five instances for each noun?
For my project, I'm using TiMBL. The results for the data are: http://pastebin.com/5wai65i1
 A: I'm a little unclear on your motivation for this (if it's for an actual application, wouldn't a dictionary be easier?), but it could be a neat computational linguistics project if you're trying to "rediscover" the rules or find patterns in the irregular ones.
Although you're getting reasonable performance (mean AUC=0.7), I think you should rethink how you generate both the features and the class labels. 
If you look at the confusion matrix at the end of your results, a lot of the 'f5' examples are misclassified as 'f4', 'f3', 'f2', and 'f1'. It seems weird to count these as incorrect, since it's getting the gender correct (good!), but the suffix length wrong (do you actually care?). If you don't, maybe just recode them as 'f' and 'm', which should be easy enough with find and replace.
As for the features, it seems like it'd be better to have multiple features per instance. If you are testing the hypothesis that gender is encoded in the suffix, I would be tempted to try making each of the last five letters a feature. For example, instead of doing:

esthé, t, f5, 
esthét i f4
esthéti q f3
esthétiq u f2
esthétiqu e f1

represent the same data as 
t, i, q, u, e, F #esthétique

You might need an $\emptyset$ symbol for shorter words. 
Finally, it might be neat to run this through an algorithm that gives you rules. It would cool if your learnt rules match the ones taught in French class (e.g., [don't care],e,u,s,e-->female).
A: Have a look to my website on this topic, especially the page on suffixation and gender - http://genderfrenchnouns.yolasite.com/derogation-1.php
