4th project for COMP 551 Fall 2016

Most functionalities can be run by invoking $python main.py -t where xx is the task number. The main task is number 7 where the script will go through the entire data pipeline and report performance on the models specified in the according section of the file main.py

Code for running K-means clustering can be found under folder kmean. Similar to main.py, kmean.py has several tasks that can be invoked to access the functionalities.

A shebang allows ant_colony_clusterer_v4.py to be executed directly. Despite parallel implementation the ant-colony still takes exceeding long to run. Shorter neighborhood sizes and lower iterations will reach completion, albiet with impaired clusters.

run $python rnn_example.py

Data set: Common Eider Petersen Alaska 2000-2009

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