Ronak Desai, Kalven Bonin, Shidhesh Supekar
Is it possible to classify a recipe’s cuisine type just from a list of
ingredients? Our project seeks to answer this question and
does so using some basic tools of Natural Language Processing.
We take a dataset from Kaggle.com that has a list of ~40,000
recipes with a cuisine type classification. One method we
employ is called a Bag of Words (BoW) model which take all
words found in the ingredients list and builds a classifier based
on the occurrences of those words in the training set. The other
method is the Term Frequency-Inverse Document Frequency
(TF-IDF) which considers the frequencies of individual words in
the training set. Both methods produced a testing accuracy of
greater than 60%, which is good considering that we
implemented the most naïve NLP models.