traffic-speed-prediction

Kaggle In class competition link

Final standings

After removing duplicated teams:

• Public Leaderboard: 8/191 -> 5th
• Private Leaderboard: 12/191 -> 8th

Competition Description

The dataset provides the average traffic speed per hour for a major road in Hong Kong from 2017 to 2018. Part of the dataset is provided as the training data, and your task is to predict the rest. 80% of the dataset is provided as the training data and 20% as the testing data, including the timestamp and the corresponding average speed. We sampled the testing data only from the year 2018 to provide you a training dataset that has the complete data spanning the year 2017. However, the speed information is sometimes missing due to device malfunction.

You have to submit the predicted results of these testing samples, which are then compared with the ground truth to evaluate the performance of your model.

Evaluation Metric

The evaluation metric used is the mean-squared error. Lower error leads to a higher ranking.

Dependencies

python 3.X

pip install numpy, pandas, xgboost, sklearn

Steps to reproduce

1. Write the file path marked as g_drive in the notebook file
2. Run every cell
3. submit the newly created csv!