LibSVM data preparation problem
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Hello all,
I just started to work with LibSVM and have a problem:
I have all the data I want to work with (image features), but dont know how to make LibSVM data file.
When using libsvmwrite to transfer for example Matlab matrix into LibSVM data file, I get "Instance_matrix must be sparse" error.
Thank you in advance, Matija.
2 commentaires
Walter Roberson
le 16 Jan 2012
Any matrix can be converted to a sparse matrix using the sparse() call.
med djo
le 11 Jan 2017
Assuming that you have three different classes (1,2,3). The first class contains two samples, the second contain one, the third contain one. From each class, you will extract two values (Average and median) of the color (for example). It will give you that: classe 1: (15, 20) classe 1: (16, 21) classe 2: ( 18, 22) classe 3: (22, 24) . On matlab, we make a matrix (Matrix for learning), which contains two columns, four lines and which contain (15, 20; 16, 21;18, 22; 22, 24). And we made a matrix composed of a single column (label matrix), this matrix (1, 1, 2, 3). We execute learning SVM with SVMtrain from libSVM. The parameters I have given you as an example correspond to the RBF kernel. The gamma value, c (varies between 10 and 100,000). Please, can you help me to execute this scenario in Matlab using LibSVM??
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Matija
le 16 Jan 2012
1 commentaire
med djo
le 11 Jan 2017
Assuming that you have three different classes (1,2,3). The first class contains two samples, the second contain one, the third contain one. From each class, you will extract two values (Average and median) of the color (for example). It will give you that: classe 1: (15, 20) classe 1: (16, 21) classe 2: ( 18, 22) classe 3: (22, 24) . On matlab, we make a matrix (Matrix for learning), which contains two columns, four lines and which contain (15, 20; 16, 21;18, 22; 22, 24). And we made a matrix composed of a single column (label matrix), this matrix (1, 1, 2, 3). We execute learning SVM with SVMtrain from libSVM. The parameters I have given you as an example correspond to the RBF kernel. The gamma value, c (varies between 10 and 100,000). Please, can you help me to execute this scenario in Matlab using LibSVM??
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