Hands-on text labeling using Logistic Regression

Text labeling is a crucial task in NLP, enabling the categorization of textual data into predefined classes or sentiments. Logistic Regression, a popular machine learning algorithm, proves effective in text classification scenarios. In the following code, we walk through the process of using Logistic Regression to classify movie reviews into positive or negative sentiments. Here’s a breakdown of the code.

Step 1. Import necessary libraries and modules.

The code begins by importing the necessary libraries and modules. These include NLTK for NLP, scikit-learn for machine learning, and specific modules for sentiment analysis, text preprocessing, and classification:

    from nltk.corpus import stopwords
    from nltk.stem import WordNetLemmatizer
    from sklearn.feature_extraction.text import TfidfVectorizer
    from sklearn.model_selection import...