General Infomation

This brick provides a tool to handle missing values in your data.

It is pretty common for a data set to have missing values. This cases should be treated accordingly to not cause any issues or errors while training (e. g., some models do not support empty elements or will cause performance deterioration).

There are several ways to handle missing values: fill "cells" with function value or specify a constant one, delete rows with missing values or delete an entire column. It is highly advised to analyze your subject area (or to contact an expert if possible), as well as to get columns' information value.

There are some recommendations to consider while choosing the method to handle missing values:

• Be mindful when choosing a value or a function to fill the missing value. Always pay attention to the data types.
• Row deletion is suggested if you have a large dataset or if your subject area (e. g., medicine) allows that.
• Deleting columns is suggested if you have a large percentage of empty values and if your subject area does not forbid that. In addition, check the information value of this column to ensure that your model would not lose any useful features.

If you are not sure which method to choose, you can use brick's auto-suggestions (you will also get these suggestions when you first open the brick's settings) and then adjust them.

Description

Brick Location

Bricks → Analytics → Features Engineering → Missing Values Treatment

Bricks → Use Cases → Credit Scoring → Features Engineering → Missing Values Treatment

Bricks → Use Cases → Demand Forecasting → Data Processing → Missing Values Treatment

Brick Parameters

• Treatment

  In this parameter you can specify one of the treatment types:

  • Fill with custom value
  • Fill with function
  • Delete columns
  • Delete rows

• Value

  Enabled only if treatment type is either 'Fill with custom value' or 'Fill with function'.

  If treatment is 'Fill with function' then you need to chose one of these functions:

  • Min
  • Max
  • Mean
  • Median
  • Mode
  • Forward fill
  • Backward fill

  With 'Fill with custom value' you would need to specify the value.

• Brick frozen

  This parameter enables the frozen run for this brick. It means that all columns with the 'Fill with function' (min, max, mean, median, mode) treatment type will save their current calculated value for the next runs, which may be useful after pipeline deployment.

  This option appears only after successful regular run.

Brick Inputs/Outputs

• Inputs

  Brick takes the data set without any restrictions.