12_ Decision tree

12_ Decision tree (Decision tree)

In this chapter , We will learn another famous machine learning algorithm ： Decision tree . The decision tree itself is very simple , There is no complicated mathematical model behind it ,
But there are many skills to use decision trees well . We will learn more about what entropy model is , What is Gini coefficient , How to use decision tree to solve classification problem ,
How to get the probability of classification , How to use decision tree to solve regression problem , And considerations for using decision trees . …

12-1 What is a decision tree

12-2 Information entropy

12-4 The gini coefficient

12-5 CART And the super parameters in the decision tree

Can pass DT Refer to the relevant parameters in the official documents of
Official documents ：https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html#sklearn.tree.DecisionTreeClassifier

12-6 Decision trees solve regression problems

12-7 Limitations of decision tree

• The division of data can only be vertical or parallel
  
  
  
• Sensitive to individual data