Decision Trees: Classification

Explores decision trees for classification, entropy, information gain, one-hot encoding, hyperparameter optimization, and random forests.

Covers decision tree classification using KNIME Analytics Platform for data preprocessing and model creation.

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

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

Discusses decision trees and random forests, focusing on their structure, optimization, and application in regression and classification tasks.