As part of our data cleaning process, we want to clean up the missing data. As we have already seen, there are 351580 values for the WeatherType. So, using the Clean Missing Data option, we are going to remove the missing data.
There are a number of techniques that can be used to clean data, and this is where a data scientist comes into the picture. Based on the type of data and the weightage of data in deriving the model, a technique is selected.
Remember that the way we clean our data also adds to the quality of the data model and thus the accuracy of the prediction. Take a look at the video titled Is your data ready for data science? (https://docs.microsoft.com/en-in/azure/machine-learning/studio/data-science-for-beginners-is-your-data-ready-for-data-science ...
