Gleam Lab · Tag Archive
Tag: decision-tree
5 articles collected by topic for tutorials, cases, engineering practice, and research notes.
Big Data 203 - sklearn Decision Tree Pruning Parameters
Common parameters for decision tree pruning (pre-pruning) in engineering: maxdepth, minsamplesleaf, minsamplessplit, maxfeatures, minimpuritydecrease.
Big Data 201 - Decision Tree from Split to Pruning
Decision tree is a tree-structured supervised learning model, commonly used for classification and regression tasks.
Big Data 202 - sklearn Decision Tree Practice: criterion, Graphviz Visualization & Pruning
Complete flow of DecisionTreeClassifier on load_wine dataset from data splitting, model evaluation to decision tree visualization (2026 version).
Big Data 199 - Decision Tree Model Explained: Node Structure, Conditional Probability & Shannon Entropy
Tree model is a widely used algorithm type in supervised learning, can be applied to both classification and regression problems.
Big Data 200 - Decision Tree Information Gain Detailed
Scenario: Use information entropy/information gain to explain why decision tree selects certain column for splitting, and use Python to reproduce "best split column".