Data Preprocessing

The data can be preprocessed using the following methods:

  • Missing values threshold: remove features with more than a specified percentage of missing values

  • Log2 transformation: transform the data using the log2 function

  • Imputation: impute missing values using the

    • Mean, Median, or Mode

    • Constant Value Imputation

    • Minimum Value Imputation

    • Iterative Imputation

    • Mice Forest Imputations

  • Scaling: scale the data using the

    • Standard Scaler

On the same page it is possible to preview or download the preprocessed data as a CSV file.