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##Project Cats vs. Dogs (Columbia University STAT W4249 Applied Data Science Project 3, Spring 2016)

####Team Members:

• Gu, Xinghao
• Islam, Schinria Rema
• Lau, Arnold Chua
• Zhou, Yi
• Zhu, Yibo

Summary: In this project, we used spatial color histograms and elliptic Fourier analysis to construct features out of the Oxford-IIIT Pet Dataset (http://www.robots.ox.ac.uk/~vgg/data/pets/) and fit a binary classification model with adaptive boosting to distinguish between cats and dogs.

Contribution Statement: Lau developed the baseline classification model for evaluation (a linear support vector machine with global color histogram features). Lau, Gu and Zhu constructed the new features. Gu, Zhu, Islam and Zhou conducted model selection and assessment. Lau conducted code testing and debugging. All team members prepared the presentation. All team members approve our work presented in our GitHub repository including this contribution statement.