Source

sleipnir / tools / SVMperfer / SVMperfer.ggo

package	"SVMperfer"
version	"1.0"
purpose	"Wrapper for SVM perf"

section "Main"
option	"labels"				l	"Labels file"
										string	typestr="filename"	no
option	"output"				o	"Output file "
										string	typestr="filename"  no
option	"input"					i	"Input PCL file "
										string	typestr="filename"  yes
option	"model"					m	"Model file"
										string	typestr="filename"  no
option	"test_labels"			T	"Test Labels file"
										string	typestr="filename"	no
option  "all"       			a   "Always classify all genes in PCLs"  
										flag off

option  "slack"       			S   "Use slack rescaling (not implemented for ROC loss)"
										flag off

section "Options"
option "verbosity"  			v   "Sets the svm_struct verbosity"
										int default="0" no
option "skip"      				s   "Number of columns to skip in input pcls"
										int default="2" no
option	"normalize"				n	"Normalize PCLS to 0 mean 1 variance"
										flag	off
option	"cross_validation"		c	"Number of cross-validation sets ( arg of 1 will turn off cross-validation )"
										int default="5" no
option "error_function" 		e   "Sets the loss function for SVM learning: Choice of:
0\tZero/one loss: 1 if vector of predictions contains error, 0 otherwise.
1\tF1: 100 minus the F1-score in percent.
2\tErrorrate: Percentage of errors in prediction vector.
3\tPrec/Rec Breakeven: 100 minus PRBEP in percent.
4\tPrec@k: 100 minus precision at k in percent.
5\tRec@k: 100 minus recall at k in percent.
10\tROCArea: Percentage of swapped pos/neg pairs (i.e. 100 - ROCArea).\n" 
										int default="10" no

option "k_value"    			k   "Value of k parameter used for Prec@k and Rec@k in (0,1)"
										float default="0.5" no
option "tradeoff"    			t   "SVM tradeoff constant C"
										float default="1" no
option "simple_model"			A   "Write model files with only linear weights"
										flag	on
option "params"   				p   "Parameter file"
										string  typestr="filename"   no
option	"mmap"					M	"Memory map binary input"
										flag	off
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