Predicting traffic using Extremely Random Forest regressor

Let's apply the concepts we learned in the previous sections to a real world problem. We will be using the dataset available at: https://archive.ics.uci.edu/ml/datasets/Dodgers+Loop+Sensor . This dataset consists of data that counts the number of vehicles passing by on the road during baseball games played at Los Angeles Dodgers stadium. In order to make the data readily available for analysis, we need to pre-process it. The pre-processed data is in the file traffic_data.txt. In this file, each line contains comma-separated strings. Let's take the first line as an example:

Tuesday,00:00,San Francisco,no,3

With reference to the preceding line, it is formatted as follows:

Day of the week, ...

Get Artificial Intelligence with Python now with the O’Reilly learning platform.

O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.