Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Decision tree learning

Related lectures (32)

Decision Trees: Regression and Classification Log in to Mediaspace to watch this video

Covers decision trees for regression and classification, explaining tree construction, feature selection, and criteria for induction.

Introduction to Data Science Log in to Mediaspace to watch this video

Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.

Regression Models: Performance and Evaluation Log in to Mediaspace to watch this video

Explores regression model performance, learning errors, and building regression trees using the CART algorithm.

Ensemble Methods: Random Forests Log in to Mediaspace to watch this video

Covers ensemble methods like random forests and Gaussian Naive Bayes, explaining how they improve prediction accuracy and estimate conditional Gaussian distributions.

Recurrent Neural Networks: Language Detection Log in to Mediaspace to watch this video

Explores language detection using Recurrent Neural Networks and supervised learning concepts.

Supervised Learning: Regression Methods Log in to Mediaspace to watch this video

Explores supervised learning with a focus on regression methods, including model fitting, regularization, model selection, and performance evaluation.

Decision Trees: Induction and Pruning Log in to Mediaspace to watch this video

Explores Decision Trees, from induction to pruning, emphasizing interpretability and automatic feature selection strengths, while addressing challenges like overfitting.

AdaBoost: Decision Stumps Log in to Mediaspace to watch this video

Explores AdaBoost with decision stumps, discussing error rules, stump selection, and the need for a bias term.

Image Classification: Decision Trees & Random Forests Log in to Mediaspace to watch this video

Explores image classification using decision trees and random forests to reduce variance and improve model robustness.

Decision Trees and Boosting Log in to Mediaspace to watch this video

Introduces decision trees as a method for machine learning and explains boosting techniques for combining predictors.

Supervised Learning: Classification Algorithms Log in to Mediaspace to watch this video

Explores supervised learning in financial econometrics, emphasizing classification algorithms like Naive Bayes and Logistic Regression.

Ensemble Methods: Random Forest Log in to Mediaspace to watch this video

Explores random forests as a powerful ensemble method for classification, discussing bagging, stacking, boosting, and sampling strategies.