- 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
- Bot Security Program
- Business Process
- Finance & AccountingHuman Resources
- Automation Type
- Last Updated
- November 19, 2020
- First Published
- June 26, 2020
- Enterprise Version
- Community Version
See the Bot in Action
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.