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Source Code for 'A novel formulation of trace ratio linear discriminant analysis' (T-NNLS)

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TRLDA

To use the function "TRLDA" or "ODLDA", please follow the input/output format:

[ W ] = TRLDA( Sw,Sb,m,alpha,d,t) [ WW,W1,s,fw ] = ODLDA( Sw,Sb,d,t)

Sw : dd intra-class scatter matrix Sb : dd inter-class scatter matrix, d is the dimension of samples m : subspace dimension, m < d alpha : Relaxation factor t : iteration times W : dm projection matrix WW : 1d cell array, i-th cell indicates the projection matrix W ∈ R^{di} W1 : projection matrix with the optimal subspace dimension s : ((Tr(W'SbW))^0.5)/(Tr(W'SwW)) fw : dt, the objective function values

Please make sure that the documents Eu2_distance.m and ClusteringMeasure.m are in the same folder as TRLDA.m and ODLDA.m

Use the codes, please cite Wang J, Wang L, Nie F, et al. A novel formulation of trace ratio linear discriminant analysis[J]. IEEE Transactions on Neural Networks and Learning Systems, 33(10), pp. 5568-5578, 2022.

If you have any questions, please connect wanglinjun@mail.nwpu.edu.cn

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Source Code for 'A novel formulation of trace ratio linear discriminant analysis' (T-NNLS)

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