To build a regression model to predict the visibility distance based on the given different climatic indicators in the training data.

Data Description: This dataset predicts the visibility distance based on the different indicators as below:

1. VISIBILITY - Distance from which an object can be seen.
2. DRYBULBTEMPF-Dry bulb temperature (degrees Fahrenheit). Most commonly reported standard temperature.
3. WETBULBTEMPF-Wet bulb temperature (degrees Fahrenheit).
4. DewPointTempF-Dew point temperature (degrees Fahrenheit).
5. RelativeHumidity-Relative humidity (percent).
6. WindSpeed-Wind speed (miles per hour).
7. WindDirection-Wind direction from true north using compass directions.
8. StationPressure-Atmospheric pressure (inches of Mercury; or ‘in Hg’).
9. SeaLevelPressure- Sea level pressure (in Hg).
10. Precip Total-precipitation in the past hour (in inches).

Apart from training files, we also require a "schema" file from the client, which contains all the relevant information about the training files such as: Name of the files, Length of Date value in FileName, Length of Time value in FileName, Number of Columns, Name of the Columns, and their datatype.

Krishna Heroor