Preparing the dataset
Preparing a dataset is a crucial phase in any ML project because it has implications for the effectiveness of the trained model.
In this recipe, we will put into action two techniques to make the dataset more suitable to get a more accurate model. These two techniques will balance the dataset with standardization and bring the input features into the same numerical range.
The following Colab file (see the Preparing the dataset section in the following repository) contains the code referred to in this recipe:
preparing_model.ipynb:
Getting ready
The temperature and humidity of the last three hours are our input features. If you wonder why we use the last three hours' weather conditions, it is just so we have more input features and Increase the chance of higher classification accuracy.
To get ready for the dataset preparation...
