Decision Tree Classifier

Accelerate business decision making by making taking advantage of decision tree classifiers to improve data visualizations and make data-driven decisions.

Top Benefits

  • Increase productivity by accelerating decision making processes by up to 40%
  • Optimize decision processes throughout the organization when decisions can be made from non-linear rule based inputs
  • Reduce the turnaround time of making decisions, that can now be backed by solid data.
  • Easy to maintain solution as the bot leverages the serverless function architecture of Azure.


  • The Bot takes in the CSV file and performs a linear regression - resulting in an Excel document for further review
  • Each internal node of the decision tree denotes an attribute and each leaf node denotes a class label.
  • This bot serves as a potential companion to analytics for classification type problems

The Decision Tree Classifier bot is designed to streamline business decision making. It does this by leveraging Microsoft Azure serverless function architecture to perform a linear regression on a provided input CSV file. The produced result is a Microsoft Excel file with predicted targets enabling business leaders to quickly and easily make data-driven decisions.

Predictions in the prediction class
Ex: The below result output shows the two classes:

○ Gold_Class: This column is taken as the predicted target
○ Predicted_Class: This tells us the predicted type of the person salary i.e. it is above 50k or below it

Get Bot


Bot Security Program
Level 1
Business Process
Automation Type
Last Updated
November 19, 2020
First Published
June 26, 2020
Community Version

See the Bot in Action

Bot Logic
Sample Input File
Sample Output File
Bot Logic
Sample Input File
Sample Output File

Setup Process


Download the Bot and follow the instructions to install it in your AAE Control Room.


Open the Bot to configure your username and other settings the Bot will need (see the Installation Guide or ReadMe for details.)


That's it - now the Bot is ready to get going!

Requirements and Inputs

  • Path: Path of the CSV file.
  • NoOfColumn: Number of Columns in the CSV file.
  • InputColumn: Header of the input columns of the CSV file.
  • InputColumnDataType: Data Types of the input column (Available datatype: Numeric, String, Date).
  • MissingNumberValueReplacement: By which value you have to replace the missing number values.
  • MissingStringValueReplacement: By what string you have to replace the missing string values.
  • IgnoreColumns: header of the Columns which you have to ignore in the model.
  • PredictionColumnName: Header of the Column on which you want to predict.