Machine Learning
Logistic Regression Text Classification
A tweet text classification project that moves from a dummy baseline to logistic regression with bag-of-words features, hyperparameter tuning, and coefficient interpretation.
Period
May 2026
Tools / Tech
PythonScikit-learnLogistic RegressionCountVectorizerGridSearchCVCross-validation
Why I built it
The goal was to practice building a defensible baseline before tuning a text classifier.
Links
What it includes
- Starts with a dummy classifier baseline.
- Uses CountVectorizer and logistic regression for bag-of-words classification.
- Tunes vectorization and regularization settings with cross-validation.
What I worked on
- Built baseline and logistic-regression workflows.
- Compared tuned parameters and interpreted model coefficients.
- Completed the text-classification notebook myself and used evaluation results to judge whether changes improved the classifier.
What I Learned
- Learned why a simple baseline matters for text classification.
- Practiced connecting coefficients to interpretable words.
- Improved comfort with cross-validation and hyperparameter search.