Classification Trees
To interactively grow a classification tree, use the Classification Learner app. For greater flexibility, grow a classification tree using fitctree
at the command line. After growing a classification tree, predict labels by passing the tree and new predictor data to predict
.
Apps
Classification Learner | Train models to classify data using supervised machine learning |
Blocks
ClassificationTree Predict | Classify observations using decision tree classifier (Since R2021a) |
Functions
Classes
ClassificationTree | Binary decision tree for multiclass classification |
CompactClassificationTree | Compact classification tree |
ClassificationPartitionedModel | Cross-validated classification model |
Topics
- Train Decision Trees Using Classification Learner App
Create and compare classification trees, and export trained models to make predictions for new data.
- Supervised Learning Workflow and Algorithms
Understand the steps for supervised learning and the characteristics of nonparametric classification and regression functions.
- Decision Trees
Understand decision trees and how to fit them to data.
- Growing Decision Trees
To grow decision trees,
fitctree
andfitrtree
apply the standard CART algorithm by default to the training data. - View Decision Tree
Create and view a text or graphic description of a trained decision tree.
- Visualize Decision Surfaces of Different Classifiers
This example shows how to visualize the decision surface for different classification algorithms.
- Splitting Categorical Predictors in Classification Trees
Learn about the heuristic algorithms for optimally splitting categorical variables with many levels while growing decision trees.
- Improving Classification Trees and Regression Trees
Tune trees by setting name-value pair arguments in
fitctree
andfitrtree
. - Prediction Using Classification and Regression Trees
Predict class labels or responses using trained classification and regression trees.
- Predict Out-of-Sample Responses of Subtrees
Predict responses for new data using a trained regression tree, and then plot the results.
- Predict Class Labels Using ClassificationTree Predict Block
Train a classification decision tree model using the Classification Learner app, and then use the ClassificationTree Predict block for label prediction.
- Human Activity Recognition Simulink Model for Fixed-Point Deployment
Generate code from a classification Simulink® model prepared for fixed-point deployment.
- Identify Punch and Flex Hand Gestures Using Machine Learning Algorithm on Arduino Hardware (Simulink Support Package for Arduino Hardware)
This example shows how to use the Simulink® Support Package for Arduino® Hardware to identify punch and flex hand gestures using a machine learning algorithm.