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
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