Filter characteristic selection method based on subclass problem classification ability measurement
A classification ability and problem classification technology, applied in medical data mining, special data processing applications, instruments, etc., can solve problems such as small scores
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Embodiment 1
[0050] (1) Read the classification problem dataset:
[0051] Usually classification problem dataset is a two-dimensional matrix, for example with sample classification problem datasets such as figure 1 shown, where Indicates the category of the i-th sample. Table 1 shows the expression values of some characteristic genes of some samples in the Breast Cancer Dataset, where the second row represents the sample category, the third row represents the expression value of the first feature on each sample, and so on for the other rows, and one column represents a Sample, that is, the expression value and category of each characteristic gene of a certain person. Read all the eigenvalues of each sample in the dataset into a two-dimensional array,
[0052] middle,
[0053] Read the category of each sample into a one-dimensional array C=(c 1 , c 2 ,...,c n )middle.
[0054] (2) Calculate the classification discrimination ability value of each feature for each subcatego...
Embodiment 2
[0090] Experimental result and data of the present invention:
[0091] The experimental data sets of the present invention - breast cancer (Breast), DLBCL and Leukemia3, were downloaded from http: / / www.ccbm.jhu.edu / in 2007, see references. Table 2 shows the number of categories, features and samples contained in these datasets. The traditional objective evaluation index is used to test the performance of the algorithm, which mainly includes the number of selected features and the accuracy of classification prediction. The number of features selected refers to the number of features selected by the feature selection method, and the accuracy of classification prediction is the The accuracy rate obtained by selecting a subset of features as input to the classifier. In order to verify the effectiveness of the method proposed in the present invention, the method of the present invention (referred to as RRSPFS for short) is compared with existing Filter attribute selection methods...
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