Skip to content

Latest commit

 

History

History
32 lines (22 loc) · 1.08 KB

README.md

File metadata and controls

32 lines (22 loc) · 1.08 KB
Raw

Which US Democratic Presidential Nominee said this? Warren? Biden? Sanders?

Text Classification of quotes from candidates vying to be the Democratic presidential nominee for the 2020 US presidential election.

Here, all data has been extracted from debates between candidates. I have built a NLP classification model to identify who said what for a subset of unlabeled data.

Methodology

The quotes are subjected to basic text-preprocessing steps such as

  1. Stopword removal

  2. Punctuation removal

  3. Lemmatization

  4. Tokenization using unigram

To prepare data for modeling, I performed feature engineering. Here, I engineered features which utilize count of various components of the text such as character, word, punctuation etc.

The text classification is done using Supervised & Semi-Supervised techniques. The following models were explored:

  1. Regularized Logistic Regression

  2. Random Forest

  3. XGBoost

Tools & Technology

1. NLP: nltk, TfidfVectorizer, CountVectorizer
2. ML: sklearn, xgboost, scipy
3. Visualization: Seaborn, Matplotlib
4. Exploration: Jupyter Notebooks