Method for identifying potential customers in household industry based on novel bee colony cluster algorithm
A clustering algorithm and customer identification technology, applied in character and pattern recognition, calculation, calculation model, etc., to achieve obvious recognition effect, fast convergence speed, and strong global search ability.
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[0035] The present invention will be further described in detail below in conjunction with the examples.
[0036] Such as figure 1 The overall structure of the customer identification process is shown. First, acquire data from the customer database, such as customer basic information, customer preference behavior, etc., to form training and test sample sets. The quality of the acquired data largely affects the quality of the final results; then, in order to achieve Clustering of customers, establishing a potential customer identification model, the trained model needs to be evaluated before it can be used for potential customer identification; finally, according to the constructed potential customer identification model, new visiting customers are identified, potential customers are discovered, and target marketing.
[0037] Step 1: Establish a customer identification model based on the k-means clustering method
[0038] 1.1) Given the number of clusters c;
[0039] 1.2) f...
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