Programming VIP

catalogue 1: Introduction to naive Bayes 1.1 classification method based on Bayesian decision theory   1.2 conditional probability 2: Document classification 2.1 constructing word vector from text   2.2 calculating probability from word vector 2.3 modify the classifier according to the actual situation   2.4 document ...

catalogue 2.1 decision tree 2.1.1 sample data set 2.1.2 decision tree visualization 2.2 model classification performance prediction 2.2.1 model stability 2.2.2 SE, SP and ACC classification performance prediction #Code implementation 2.1 decision tree 2.1.1 sample data set The total sample data used in this decision tree constructi ...

Decision Tree Picks Out Good Watermelons 1. ID3 Algorithmic Theory (1) algorithm core The core of the ID3 algorithm is to select the partitioned features based on the information gain and then build the decision tree recursively (2) Feature selection Feature selection means selecting the optimal partition attribute and selecting a feat ...

1, Decision tree 1. Concept Decision tree is a classification algorithm based on tree structure. We hope to learn a model (i.e. decision tree) from a given training data set and use the model to classify new samples. The decision tree can intuitively show the classification process and results. Once the model is built successfully, the cl ...

  catalogue Construction of decision tree General process of decision tree information gain   Write code to calculate empirical entropy Calculate information gain using code Partition dataset Select the best data set division method   Information gain rate Gini coefficient   Differences between ID3, C4.5 and CART I ...