Dimensionality Reduction

This work experiments with three dimensionality reduction techniques in Python.

Installation

$ pip3 install -r requirements.txt

Running

Custom hyperparameters in a textfile i.e. “./configs/config.txt”.

$ python3 experiments.py ./configs/config.txt

A results folder will contain a timestamp directory with the latest results.

This work is a experiment with a number of algorithms on several datasets.
The aim is to get a feeling of how well each of these algorithms works,
and whether there are differences depending on the dataset.

Datasets

• Iris (http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_iris.html)
• Breast Cancer (http://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(diagnostic))

Techniques

• PCA
• t-SNE
• Multi Dimensional Scaling (MDS)

Report

Dimensionality-Reduction-Alonso.pdf