Unsupervised Learning and Dimensionality Reduction
forked from - https://github.com/cmaron/CS-7641-assignments.git
Output
Output CSVs and images are written to ./output and ./output/images respectively. Sub-folders will be created for each DR algorithm (ICA, PCA, etc) as well as the benchmark.
If these folders do not exist the experiments module will attempt to create them.
Clustering Experiments
The experiments will output modified versions of the data sets after applying the DR methods. The script run_clustering.sh can be used to perform clustering on these modified datasets, using a specific number of components for the DR method.
BE SURE TO UPDATE THE VALUES IN THIS SCRIPT FOR YOUR DATASETS.
There are different optimal values for each algorithm and each dataset, and using the wrong value will make you a sad panda.
Graphing
The run_experiment script can be use to generate plots via:
python run_experiment.py --plot
Since the files output from the experiments follow a common naming scheme this will determine the problem, algorithm,
and parameters as needed and write the output to sub-folders in ./output/images.