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First Decision Tree

Exercise 2 Training Algorithms for Numeric Prediction

This workflow shows a hands-on exercise in the L4-ML Introduction to Machine Learning Algorithms self-paced course

Train and Evaluate a Decision Tree

First, a Decision Tree model is trained using the provided data. This model is then used to predict outcomes for the same dataset. Finally, the predictions are compared to the actual values to measure how accurately the model performed.

Filter and Predict on a Single Row

Selects a specific row of interest from the data, allows you to review or edit its values, and then uses the trained Decision Tree model to predict the outcome for just that row. This helps you see how the model would classify or score an individual example.

Decision Tree Predictor
Table Creator
Decision Tree Learner
Row Filter
Table Editor (JavaScript) (legacy)
Decision Tree Predictor
Scorer

Nodes

Extensions

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