Predicting cuisine category using recipe ingredients

Project Intro:

In this project, we leveraged various traditional machine learning and deep learning methods to predict the category of a dish’s cuisine given a list of ingredients that used in the dish.

Data description:

Training dataset is in JSON format and has three attributes: recipe ID (int), the type of cuisine(object/string), and the list of ingredients (object list). Test dataset only have two attributes: recipe ID and the list of ingredients. Both attributes have the same format as they appear in Training dataset.

Data Preparation & Feature Engineering:

• Since the format of both training and testing dataset is the combination of string and numeric, we have to somehow convert string into numeric value for modelling.
• Removing the special characters, numbers and units(if any) in each ingredient, those may affect the true value when converting to numeric.
• Standardized words (convert all letters to lower case, remove hyphen, change word to default tense)
• Using TF-IDF algorithm to extract some significant(unique) ingredients for each recipe and convert to numeric value, this will be the features for that recipe. The result matrix is a sparse matrix.
• Since the matrix after TF-IDF is a spare matrix with a large dimension, we consider SVD method to reduce the dimension. In this case, we perform truncated SVD algorithms.

Modelling:

• Logistic Regression with OVR
• Support Vector Machine with OVR and linear boundary (using linear boundary due to hardware limitation)
• Random Forest
• Boosting and voting classifier
• Neural Networks
• Hyper-parameter tuning is done via GridSearchCV in Python. Random Forest and boosting & voting classifier is not reported due to low accuracy on validation dataset.

The code for this project can be found at this url

Original Kaggle Competition link

If you want to use the code, or find our project useful, you can set as follows:

@misc{mz2020whats,
    author = {Zhou, Meng},
    title = {What's Cooking: Predicting cuisine category using recipe ingredients},
    year = {2020},
    howpublished = {\url{https://simonzhou86.github.io/portfolio/whats_cooking}},
}