# gini index decision tree example

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### Entropy and Giniindex in decisiontree

Decision tree is a very basic classification and regression method, but as the previous blog machine learning sorting algorithm: Ranknet to Lambdarank to Lambdamart in the Lambdamart algorithm, the most basic algorithm is a lot of classic, complex, The basis of an efficient machine learning algorithm. About what is a decision

### Decision trees-predicting contact lens types (ID3 algorithm, C4.5 algorithm, cart algorithm, Giniindex, pruning, random forest)

The above example is a property with 8, and each property has multiple discrete values. On each node of the decision tree we can divide by any one of the values of any one of these properties. For example, at the beginning we press: 1) surface covering for hair and non-fur 2) surface c

### DecisionTree algorithm-Information entropy-information gain-information gain rate-gini coefficient-turn

1. Introduction to the algorithm backgroundThe classification tree (decision tree) is a very common classification method. He is a kind of supervised learning, so-called regulatory learning is simple, that is, given a bunch of samples, each sample has a set of attributes and a category, these categories are predetermined, then by learning to get a classifier, the

### Sklearn database example-DecisionTree Classification and sklearn database exampleDecision-Making

Sklearn database example-Decision Tree Classification and sklearn database example Decision-Making Introduction of decision tree algorithm on Sklearn: http://scikit-learn.org/stable/mod

### Using whether to buy a house as an example to illustrate the use of decisiontree algorithm-ai machine learning

We take the purchase of housing as an example to introduce the use of decision tree algorithm, the data set is as follows (demo only, does not represent the real situation) Lot Near Subway Area Unit Price (million) Whether to buy Three Rings Is 60 8 Is Three Rings Is 80

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