I want to build a basic language detector for English, French and German.
I went to wikipedia and I downloaded the page of 'Technology' in all these languages.
In all these cases, we are talking for about 10000 words.
So basically I have 3 documents of 10000 words each for each of the 3 languages above.
My question is the following:
Should I split these documents in smaller documents e.g. of 100 words and create in this way more labeled observations in my dataset or should I leave them like this for training my classifier (e.g. with a TF-IDF model)?