Skill

Decision Tree Learning

Data Science, Analytics and AI/ML

Decision tree learning is a supervised machine learning method that builds a tree-like model of decisions by recursively splitting data based on feature values to predict an outcome or classification. Algorithms like ID3, C4.5, and CART are used to construct these trees by choosing splits that maximize information gain or minimize impurity. Data scientists use it for both classification and regression tasks because the resulting models are interpretable and easy to visualize.

Open roles requiring Decision Tree Learning (0)

None of the roles we’ve read name this skill yet. Browse all open roles.

• Supervised Learning
• scikit-learn
• Decision Trees
• Feature Engineering