Road Trip Recommendations
Using the Yelp Academic Dataset, Python, and scikit-learn, I worked with Jocelyn Hickhox to implement an algorithm that provides restaurant recommendations for someone on a road trip given an origin, a destination, and various desired attributes. This was done as part of a project for CS 221 (Artificial Intelligence) at Stanford University.
Released under the MIT license (see LICENSE
).
Examples
Loading saved restaurants
Limiting restaurants
Constructing features
Calculating scores and establishing datasets
Baseline: pick restaurant with lowest distance and highest rating
Baseline recommends:
Pete's Fish & Chips 3715 E Van Buren St
Phoenix, AZ 85008 -112.001533 33.45111
This adds a distance of 0.021151 km away with a 3.0-star rating
Running regression against training set
Predicting test set
Average percent error 20.8014599346
Regression recommends:
Pozoleria Guerrero 2801 E Van Buren St
Phoenix, AZ 85008 -112.021191 33.451004
This adds a distance of 0.100828 km away with a 4.5-star rating