musama619/DataPreProcessing_2

Data-Preprocessing

Data Preprocessing part 1: https://github.com/musama619/DataPreProcessing

• Handling Missing Data
  

• Encoding Independent Variables
  

  OneHotEncoder
  

• Encoding Dependent Variable
  

  LabelEncoder
  

• Train - Test Split
  

• Feature Scaling
  

  Standardisation

Note:

1. Standardisation : values between -3 and 3 (works all the time)

2. Normalisation : values between 0 and 1 (recommended only when features follows normal distribution)

• remember to apply feature scaling after train test split
• feature scaling does not need to be applied on dummy variables as they already have values between -3 and 3

Important link:

• https://medium.com/@contactsunny/label-encoder-vs-one-hot-encoder-in-machine-learning-3fc273365621#:~:text=What%20one%20hot%20encoding%20does,which%20column%20has%20what%20value.&text=So%2C%20that's%20the%20difference%20between%20Label%20Encoding%20and%20One%20Hot%20Encoding.