A Matrix Classification Model Based on Between-Class Discrimination

A matrix pattern and matrix technology, which is applied in the field of learning machine models based on inter-class discrimination matrix, can solve the problem of not considering the discriminative information between matrix patterns and other classes, and achieve the effect of improving the overfitting problem and improving the classification accuracy.

Active Publication Date: 2020-07-14
EAST CHINA UNIV OF SCI & TECH
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Problems solved by technology

[0005] For the problem that the existing matrix pattern-oriented classifier design method does not take into account the discriminative information between the matrix patterns, the solution of the present invention is to design a new regularization term to consider discriminative information between classes, resulting in a locally sensitive discriminant matrix learning model

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  • A Matrix Classification Model Based on Between-Class Discrimination
  • A Matrix Classification Model Based on Between-Class Discrimination
  • A Matrix Classification Model Based on Between-Class Discrimination

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Embodiment Construction

[0010] The present invention will be further introduced below in conjunction with the accompanying drawings and embodiments. The method of the present invention is divided into three major steps.

[0011] The first step: data set collection and transformation,

[0012] First process the collected data set, digitize the non-numerical data set, grayscale the image data set, and then use the dimensionality reduction algorithm to reduce its dimensionality for subsequent processing. Secondly, matrix the collected data set, for example, x∈R 1×N Converting it into a matrix sample is where d 1 × d 2 =N.

[0013] Step 2: Model training

[0014] 1) First construct the regularization term R BC

[0015] Assume that the matrix pattern of the binary classification is and the class of each pattern is Use the clustering method to cluster each category separately, and calculate its cluster center as in equation (1):

[0016]

[0017] where the number of clusters of each class...

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Abstract

The invention provides a matrix classification model based on inter-class discrimination. First, data sets are collected, and the collected samples are converted into matrix-type samples, and then regularization items are constructed. Then the regularization term is introduced into MatMHKS, and a new matrix-oriented pattern classification model CBCMatMHKS is generated, and the new model is trained with the training set. In order to obtain the optimal solution of the model, we use the gradient descent method to solve the model CBCMatMHKS. Then use the test set to test the obtained optimal solution, and then obtain the optimal decision function. Finally, the optimal decision function is used to calculate the input matrix samples that need to be judged, and classify the matrix samples according to the output results. Compared with the traditional matrix classification model, the method of the present invention introduces discriminative information between classes and uses cluster centers to represent samples in a certain area to maximize the distance between samples of different classes and improve its classification. Correct rate.

Description

technical field [0001] The invention relates to the field of pattern recognition, in particular to a method for learning a machine model based on an interclass discrimination matrix. Background technique [0002] At present, most classifiers can only process vector-type samples, and matrix-type samples need to be converted into vector-type samples before they can be processed. For example, for a face picture, a vector-type classifier needs to convert it into a vector-type sample before processing it, but this loses the structural discrimination information inside a single sample to a certain extent. The design method of matrix pattern classifier can directly classify matrix samples. At the same time, experiments show that the design method of matrix pattern classifier can effectively improve the performance of vectorization classifier design method to a certain extent. [0003] The original matrix pattern classifier design method ignores the discriminative information betw...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62
CPCG06F18/243
Inventor 王喆李冬冬张国威高大启
Owner EAST CHINA UNIV OF SCI & TECH
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