What are the methods of data mining?

The methods of data mining mainly include the following points:

1. Classification mining method. Classification mining method mainly uses decision tree to classify, which is an efficient mining method and occupies an important position in data mining methods. In order to test and classify the data accurately, we use the decision tree algorithm. Several typical methods in the decision tree are: ID3 algorithm, which is practical and suitable for large-scale data processing; KNN algorithm, this method has a large amount of calculation and is suitable for different types of data processing.

2. Clustering analysis mining method. Cluster analysis mining method is mainly used in the research field of sample and index classification. It is a typical statistical method and widely used in business field. This clustering analysis method can be divided into four analysis and mining methods according to different applicable objects: grid-based clustering analysis method, hierarchical clustering method, density-based clustering mining method and model-based clustering method.

3. Forecast method. Prediction methods are mainly used to predict knowledge and mine continuous numerical data. Traditional forecasting methods are mainly divided into time series method, regression model analysis method and grey system model analysis method. At present, neural network and support vector machine algorithm are mainly used to analyze and calculate the data, and at the same time, the trend of future data can be predicted.

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