基于决策树方法的分类规则的挖掘（Mining of classification rules based on decision tree method）.doc

基于决策树方法的分类规则的挖掘（Mining of classification rules based on decision tree method） Mining of classification rules based on decision tree method Categories: AUTO - HTML The fifth author: wang shuyan Abstract: Data mining is motivated by the decision support problem faced by some large retail organizations. A lot of sales data collected by barcode technology is the foundation of mining. Through mining on these data, we can find some information for commercial sale and production of extremely effective (the information reflected by specific model), which can improve the efficiency of sales and production, reduce costs, maximize business benefits, this is the meaning of data mining. This article mainly introduces a pattern in data mining: the classification rule based on the decision tree method. The algorithm of C4.5 is also given in detail 1 research background 1.1 term The definition of KDD technology: KDD is the process of extracting credible, novel, effective, and understandable patterns from a large number of data. This process is a high-level process. Usually KDD includes data preparation, data mining, and the interpretation and evaluation of results. Data mining is according to the requirements of the decision, to determine the task and purpose of data mining, and by using the data mining algorithm of the specific process of digging out the useful knowledge from data set, is the key link in KDD, is the main topics of the KDD research. Typically, we do not distinguish between KDD and data mining. Data Mining, Data Mining,) is from large, incomplete, noisy, fuzzy, random practical application in the Data, extract implicit in it, people dont know in advance, but it is potentially useful information and knowledge of the process. 2. Analysis of classification rules 2.1 classifier The problem of classification is to classify an event or object. You can use this model to analyze existing data and use it to predict future data. The concept of classification is to learn a cla