Portfolio Assignment 2

Similarity Metrics

Summary

Add a .html file to your portfolio titled Similarity Metrics.

Purpose & Requirements

Demonstrate your knowledge of calculating similarities by describing a handful of similarity metrics and illustrate your understanding by providing example code. Your writing should include:

• An introduction that summarizes what we mean by "calculating similarity."
• Brief sections for each similarity metric (listed below)
• Each section should include the metric's title, a short description and common use cases (eg, when is Jaccard typically used? When is SMC typically used?)
• Where possible, provide example implementations (your code) of each metric.

The similarity metrics you present should include any three of:

• Euclidean distance
• SMC
• Jaccard
• Tanimoto
• Pearson Correlation
• Cosine similarity

This document should be equivalent to two or three double-spaced, typewritten pages in length. Be brief, but thorough -- the reader should have a good understanding about the various metrics, and believe that you have a strong understanding of them.

Grading Criteria (250 points)

Your portfolio must contain a table of contents in index.html and have one link called Similarity Metrics; and one page called similarity.html that fulfills the requirements described above.