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us107/Uber-Ride-Predictions--A-Data-Analysis-Project

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This project aims to predict various aspects of Uber rides using Logistic Regression and Random Forest models. The main objective is to compare the performance of these models using both test accuracy and cross-validation accuracy.

active 2024-11-252024-11-25 (UTC)

Partial coverage24,591 / 26,317 hourly files (93%) · 2 absent upstream · 1,725 failed, retryable2023-08-152026-08-15 (UTC)— sampled evenly across the window, so rankings and trends hold; absolute counts scale up.
Events
4
Pushes
2
Pull requests
0
Issues
0
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 1 days from 2024-11-25 to 2024-11-25. Pushes: 2 total, peak 2 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.

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  • Stars

Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

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us1072200

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No issue or PR events — this repo's activity is pushes only.

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.