Method for realizing tobacco sales abnormal behavior detection based on isolated forest model
A forest model and anomaly detection technology, which is applied in the field of tobacco and sales behavior anomaly detection, can solve problems such as difficulty in collecting data volume and data labels, seldom consider the characteristics of the prediction object itself, and the difference in prediction results, etc., to achieve the maximum utilization of information The effects of modernization, effective decision support, and high recall rate
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[0027] In order to describe the technical content of the present invention more clearly, further description will be given below in conjunction with specific embodiments.
[0028] The method for detecting abnormal behavior of tobacco sales based on the isolated forest model of the present invention comprises the following steps:
[0029] (1) Preprocessing the data set;
[0030] (2) Perform feature extraction on the data set;
[0031] (3) Build an isolated forest model;
[0032] (3.1) Randomly extract ψ sample points from the data sample population to form a subset, and put them into the root node of the isolated tree;
[0033] (3.2) Randomly specify a feature q from all features, and randomly generate a cutting point p in the feature value of the current data feature q;
[0034] (3.3) Cut the sample space and divide the current data space into two subspaces;
[0035] (3.4) Judging whether all nodes have only one sample point or the isolated tree reaches the specified heigh...
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