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This lab exercise is about air quality analysis, where you will predict air quality through solving classification and regression tasks.
You will submit a notebook file, a pdf report, and a trained model. You will be marked for implementation,
design, result and analysis. Your code should be easy to read and your report should be concise (max 600 words).
It is strongly recommended that you use a LaTeX editor, such as Overleaf , to write your report.
Please note your notebook should take no more than 10 minutes to run on lab computers.
There is 1 mark for code efficiency.
1. Dataset and Knowledge Preparation
The provided dataset contains measurements of air quality from a multisensor device.
The device used spectrometer analyzers (variables marked by "GT") and solid state metal oxide detectors (variables marked by "PT08.Sx"),
as well as temperature (T), relative humidity (RH) and absolute humidity (AH) sensors.
The dataset contains 3304 instances of hourly averaged measurements taken at road level in a polluted city.
You will predict the CO(GT) variable representing carbon monoxide levels. There are missing features in this dataset, flagged by the number -999 .