Cheat-sheetSDDETECTOR training a detector given a target class and model [PD,R]=SDDETECTOR(DATA,TCLASS,MODEL,options) INPUT DATA a data set TCLASS target class name MODEL untrained pipeline OUTPUT PD detector pipeline R estimated ROC OPTIONS 'reject' Fraction of target class samples to reject 'target' Name of the target decision in the final detector 'non-target' Name of the non-target decision in the final detector 'test' External test set used to set detector threshold with ROC 'nodisplay' Do not display class mapping DESCRIPTION SDDETECTOR provides one-command detector training. By default it splits DATA into 80% which is used for training the MODEL on target class TCLASS. Decision threshold is fixed using ROC analysis performed on the remaining 20% of data. The SDROC object R is returned as 2nd output. If external test set is provided with 'test' option, it is used for ROC analysis (complete DATA is used for training a model). If TCLASS is not present in DATA, detector is trained on all DATA samples. In this one-class scenario, SDDETECTOR needs extra information for setting the threshold: the fraction of rejected objects (using 'reject' option). SDDETECTOR PD returns 'TCLASS' and 'non-TCLASS' decisions (may be changed using 'target' and 'non-target' options). EXAMPLES Train Gaussian detector on 'banana' and set the threshold by ROC using other classes: pd=sddetector(a,'banana',sdgauss) Train k-NN detector on all samples in a and set its threshold by rejecting 1% of samples: pd=sddetector(a,'all',sdknn([],'k',7),'reject',0.01) READ MORE http://perclass.com/doc/guide/classifiers.html#detector
sddetector is referenced in examples: