alteryx/evalml

Add support for Pipelines and Random Forests to visualize_decision_tree

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#1,680 opened on Jan 12, 2021

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enhancementgood first issue

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Description

Currently visualize_decision_tree supports only Decision Trees. We can expand the functionality to include support for Pipelines (so that the associated estimator can be taken and visualized) and for Random Forests.

Regarding Random Forests, we can choose to add the ability to view the entire forest, or to specify a tree in the forest, or both.

Contributor guide

Research direction
Study the existing visualize decision tree function to understand how it extracts and renders a single decision tree. Extend it to handle Pipeline objects by retrieving the final estimator (e.g., pipeline.steps[ 1][1]). For RandomForest, add an optional parameter (e.g., tree index) to visualize a specific tree, or iterate over all trees to display the forest. Ensure visualizations are compatible with existing plotting utilities.
Tech stack
python
Domain
machine learning
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-2 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Mostly clear
Prerequisites
PythonGit
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
55