Decision Tree

A Decision Tree Chart is a branching diagram that helps determine a course of action or visualize statistical probabilities. The chart resembles an upright or horizontal tree structure, with each branch representing possible decisions, outcomes, or reactions.

A Decision Tree is composed of three main types of nodes:

  • Decision Nodes: Represent decision points.

  • Chance Nodes: Represent uncertain outcomes.

  • Outcome Nodes (Leaves): Represent final results at the end of a decision pathway.

This makes the Decision Tree an excellent tool for predictive modeling, classification, and regression analysis, as well as for business decision-making.

Best Situations to Use

Use a Decision Tree chart when you want to:

  • Classify data based on conditions (e.g., customer churn prediction).

  • Display regression outcomes with continuous nodes as endpoints (Regression Trees).

  • Predict customer behavior or actions, such as purchase decisions.

  • Forecast financial or market trends, such as stock price movements.

  • Simplify complex decision-making processes into a structured flow.

Properties of the Decision Tree Chart

General

  • Component Name: Unique identifier for the chart.

  • Left / Top: Position of the chart within the dashboard.

  • Height / Width: Chart dimensions.

  • Initial Visibility: Toggle visibility at initial load.

  • Max Button: Enable maximize functionality.

Tooltip

  • Show Tool Tip: Enable/disable tooltip display.

  • Configuration:

    • Background Color

    • Opacity (tooltip transparency)

    • Border Color

    • Font Size

    • Box Width

Background

  • Gradient Rotation: Adjust gradient angle.

  • Opacity: Control background transparency.

  • Gradient: Select gradient type and direction (multi-color supported).

  • Border / Border Color / Border Radius: Customize border styling and curvature.

  • Shadow / Shadow Color / Transparency: Add and customize drop shadow effect.

Styling Properties

Customize the look and feel of nodes, lines, and text:

  • Node Color: Define node fill color.

  • Node Transparency / Opacity: Adjust node visibility.

  • Node Border Color: Configure border color for nodes.

  • Percent Box Color: Set fill color for probability/percentage boxes.

  • Percent Box Opacity / Border Opacity: Adjust transparency.

  • Line Color: Define the color of connecting lines.

  • Line Opacity: Control transparency of connector lines.

  • Font Color: Customize text color.

  • Font Family: Select font type for node and label text.

Export Options

  • Context Menu: Enable right-click menu for export.

  • Supported Formats: Excel (.xlsx), CSV (.csv), JPEG (.jpg), PNG (.png), PPTX (.pptx), PDF (.pdf).

  • Print Option: Directly print the chart.

  • Export Metadata: Add custom heading, subheading, and filename.

  • Global Export Type: Define default export format (Screenshot / Tabular).

Dataset Properties

When mapping data to a Decision Tree chart:

  • Decision Field: Represents decision points.

  • Outcome Field(s): Represent possible outcomes or reactions.

  • Probability / Percentage Fields: Represent statistical likelihoods for chance nodes.

Example

Using the sample dataset:

  • Decision Node: Customer Age Group.

  • Branches: Conditions based on income or product interest.

  • Leaves: Outcomes such as "Likely to Purchase" or "Not Likely to Purchase".

The resulting chart visualizes customer pathways and provides clear insights into decision outcomes.