Decision Tree Classification
Classify the categorical target variable in your dataset. A complete ML report with feature importance, confusion matrix and a tree structure visualization.
Tree Model
A decision tree is trained with the Gini or entropy criterion. You can set the maximum depth yourself.
Feature Importance
A ranked table shows which variable contributes most to the classification.
Confusion Matrix
Accuracy, precision, recall and F1 score on the test set are reported.
PDF Report
The tree structure, metrics and an APA-style report sentence are downloaded as a PDF.
How It Works?
Upload your CSV or Excel file.
The analysis completes automatically within seconds.
View the results on screen and download them as a PDF.
Create a free account and start using it right away.
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