this project aims to classify recipes to vegan, non-vegan, based on the list of ingredients. data is from Kaggle [https://www.kaggle.com/hugodarwood/epirecipes], with some changes.
- KNN (K nearest nieghbor).
- Logistic Regression.
- Decision Tree Classifier.
- Loading the CSV Data
- cleaning the data to remove punctuation + digits + non alphabetic characters. 3.convert the textual representation of information into a matrix of TF-IDF features.
- split the dataset into training and testing.
- perform the three algorithms.
from the results we can see that the Decision Tree Classifier yields the highest accuracy while KNN yields the lowest accuracy
- KNN (K nearest nieghbor) = 90.4%
- Logistic Regression = 91.3%
- Decision Tree Classifier = 91.5%