# Pre- and Post-Processing Tools

MILO provides a set of pre and post processing tools which allows users to more easily prepare and optimize their data for use within the MILO Auto-ML tool. These can be accessed from the MILO landing page (under Preprocessing Tools).

Preprocessing Tools

The tools include:

  • Train and Test Builder: Converting a single data file to the necessary two datasets (training / initial validation test and generalization test datasets when needed) that is required within the MILO Auto-ML tool.

  • Multicollinearity Assessment & Removal Tool: Allows you to observe and assess the correlations between the variables and to remove high correlates when deemed appropriate.

  • Feature Selector: As the name implies, this tool will allow you to assess and select the statistical contributions of the independent variables to the target/outcome variable through two different methods (an ANOVA F value approach and the Random Forest Importances method). This will allow you to visualize and select for the most significant features within your dataset when necessary.

  • Column Reducer Tool: Removes specific user-defined columns/features when needed.

  • Imputation & Encoder Tool : Allows you to iteratively impute missing values and encode non-numerical data into the numerical data. MILO Pro