Similarity Measures Applied to Real Data (Uber Dataset)

Project Overview

This university project explores similarity measures used to compare trajectories and time-series data using Python.

A real-world dataset (Uber trips) is used to demonstrate how similarity metrics behave on practical data.

Dataset

• Uber trips dataset (CSV file)
• Stored in the data/ folder

Similarity Measures Implemented

• Dynamic Time Warping (DTW)
• Discrete Frechet Distance
• Curve Length
• Area Between Curves
• Point Cloud Matching (PCM)
• Euclidean Distance
• Manhattan Distance
• Chebyshev Distance
• MAE and MSE

Technologies

• Python
• NumPy
• Pandas
• Matplotlib
• similaritymeasures
• Jupyter Notebook

Project Structure

.
├── similaritymeasuresprojet.ipynb
├── data/
│   └── uber.csv
├── presentation/
│   └── similarity measures.pptx.pdf