Euclidean Distances
Euclidean distance measures are central to the k-Nearest Neighbor algorithm, thus this project utilizes 5 algorithims to calculate distance point value differences and each algorithim's detailed numerical complexity analysis!
Project Utilizes:
- Pandas
- Series/Dataframes
- Loaded Operators
- Higher Order functions
- NumPy
- linalg module
- SciPy
- distance module
- Timeit
- default_timer() method
Project Features:
- Project delves into several different ways to compute the Euclidean distance between two points.
- Different algorithms are timed to help determine which method of computing Euclidean distance is the most efficient.
- Algorithm iterations to visualize the impact on the algorithm's duration.