CSCI 183 Final Project

Logistic Regression & Naive Bayes on Amazon review data

Thida Aung, Sanjay Kaliyur, Erik Trewitt

Jupyter Notebook with a Python 3.5.2 kernel. Tested and run on Mac OS X, but should be platform-independent due to the nature of Python.

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Setup instructions

0. Clone this project using git clone git@github.com:sanjaykaliyur/CSCI183-Project.git, or download the zip file from the github page.

1. If you don't already have it, install Python 3.5+ from python.org or using sudo apt-get install python3.

2. Install pip3:

• Unix: sudo apt-get install python3-pip.
• Other: Follow pip's manual installation instructions.

3. Ensure pip is up to date: pip3 install --upgrade pip.

4. Install Jupyter: pip3 install jupyter.

5. Install required dependencies: pip3 install $(cat install-requires.txt).

6. Download the compressed data files from source (Video Game and Musical Instrument 5-core), decompress them, and place them in data/.

7. Open the project notebook:
   python3 -m jupyter notebook sentiment-analysis--amazon_commented.ipynb.

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External Dependencies

• matplotlib: Data plotting tool
• nltk: Natural language toolkit, used for stemming
• pandas: Data processing toolkits
• sklearn: Machine learning algorithm library