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Imbalance sample classification method based on PSO (Particle Swarm Optimization) algorithm

A classification method and algorithm technology, which is applied in the classification field applicable to unbalanced samples, can solve the problem that the classification effect is not optimal, and achieve the effect of improving the effect and simplifying the operation

Inactive Publication Date: 2016-08-17
SHENZHEN ETTOM TECH CO LTD
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Problems solved by technology

The weight coefficients of these base classifiers often have an influence or relationship with each other, and the final classification effect obtained by simply determining their coefficients based on classification errors is often not optimal.

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  • Imbalance sample classification method based on PSO (Particle Swarm Optimization) algorithm
  • Imbalance sample classification method based on PSO (Particle Swarm Optimization) algorithm
  • Imbalance sample classification method based on PSO (Particle Swarm Optimization) algorithm

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Embodiment Construction

[0025] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0026] Particle Swarm Optimization (PSO) algorithm was proposed by Dr. Kennedy and Eberhart in 1995. It is an evolutionary algorithm, which is inspired by the group behavior of insects, herds of animals and birds in imitation of nature. These group creatures in nature will search for food, mates and other things in a way that they can understand. Each member of the group will change the individual or group by learning from their own experience and the experience of other group members. Behavioral patterns, and finally complete the global search of the group. From real examples, we can understand the specific process of the PSO algorithm: Suppose there is a group of birds searching for the location of food aimlessly in a certain area. In which direction can they fly to a location near the food, and how can these birds find the food with the opt...

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Abstract

The invention provides an imbalance sample classification method based on a PSO (Particle Swarm Optimization) algorithm. A PSO algorithm is adopted, the sampling rates of a boundary sample and a safe sample in an oversampling process are optimized to obtain an optimal oversampling multiplying power, and meanwhile, characteristics are optimized so as to select a characteristic combination which can simplify operations and improve a classification result and has best representativeness. The imbalance sample classification method adopts AUC / F-Mea as the fitness function of the algorithm so as to improve the effect of a final classifier.

Description

technical field [0001] The invention belongs to the field of classification technology optimization in data mining, in particular to a classification method applicable to unbalanced samples. Background technique [0002] In the problem of unbalanced sample classification, unbalanced data means that in the sample space of the entire data set, there is a huge gap in the number of samples of one class and the samples of the other class or classes. Often the minority class in this case requires us to devote more attention. For example, in the application of medical diagnosis, the data sample space of cancer or heart disease is an unbalanced sample. In this type of sample, the objects we pay attention to are often diseased samples. By accurately classifying the attributes of these samples, we can accurately Diagnose the patient's condition and give these patients timely and targeted treatment. [0003] In order to pursue a higher global classification accuracy when dealing with...

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Application Information

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IPC IPC(8): G06K9/62G06N3/00
CPCG06N3/006G06F18/241
Inventor 张春慨
Owner SHENZHEN ETTOM TECH CO LTD
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