SVMmulti

SVMmulti performs SVM learning using the SVM struct multiclass library. It supports cross validation and reading from binary PCL files created by PCL2Bin.

Usage

Basic Usage

 SVMmulti -l <labels_file> -p <params_file> -i <data.bin> -o <output_directory> -a

The labels file is of the format (NOTE WELL: IN ALL THE FOLLOWING FORMATS DELIMITERS ARE TABS -- doxygen converts them to spaces automatically).

 ACTA2  -1
 ACTN4  1
 ADAM10 -1
 AGRN   1
 AGTR1  -1
 ALDOB  -1
 ALOX12 1
 ANGPT2 1
 APOA4  1
 AQP1   1

where -1 indicates negative and 1 indicates positive. The examples must be separated with tabs.

Output is of the format

 IGHV1-69   0   1.94073
 DAG1   1   1.9401
 FNDC3B 0   1.93543
 HPGD   -1  1.93181
 TPSAB1 0   1.92928
 CLIC5  1   1.92759

where the first column is the example name, the second column is the gold standard status (matching labels) and the third column is the prediction from the SVM.

The params_file is of the format

 10 0.1 0.5
 10 0.01    0.5
 10 0.001   0.5
 10 0.0001  0.5
 10 0.00001 0.5
 10 0.000001    0.5

where the first column represents the error function, the second column represents the tradeoff constant and the third column represents k_value (for precision at k recall, but unused for the AUC error function in the example above.

SVMmulti can also be used to output a model or learn a network, although currently those features are undocumented.

Detailed Usage

Flag	Default	Type	Description
-i	None	PCL/BIN file	Input PCL file
-o	None	Directory	Output directory.
-l	None	Labels file	The file with examples formatted as noted above.
-m	None	Model file	If present, output the learned model to this file.
-a	off	Flag	If on output predictions for all genes in the PCL.
-S	off	Flag	If on, use slack rescaling.
-s	2	int	Number of columns to skip from PCL file.
-n	off	Flag	Normalize PCL to 0 mean, 1 variance.
-c	5	int	Number of cross validation intervals.
-e	10	int	Which loss function should be used? (options: 0, 1, 2, 3, 4, 5, 10).
-k	0.5	float	value of k for precision or recall.
-t	1	float	SVM tradeoff constant C (note that this differs from the version in SVM light by a constant factor, check SVMPerf docs for details).
-p	None	Filename	Parameters file (to test with multiple parameters).
-M	off	Flag	Memory map binary input PCLs (BIN files).