CONSTRAIN Get a subset of op.points based on performance constraints R2=CONSTRAIN(R,measure,constraint,...) [R2,IND]=CONSTRAIN(R,measure,constraint,...) Use multiple constraints in normalized confusion matrix: [R2,IND]=CONSTRAIN(R,'nconfmat',NCM) INPUT R SDROC object measure measure definition (index or name such as 'err(apple)') constraints scalar constraint value OUTPUT R2 SDROC subset fulfilling all constraints or empty IND Indices of the R2 subset in R DESCRIPTION CONSTRAIN method applies one or more constraints on the estimated measures. The measures may be specified by their index or by name. For each measure we only need to provide scalar value, the polarity is chosen automatically (errors are minimized, performances maximized). It is possible to provide multiple measures in normalized conf.matrix NCM. Fields with NaN values are ignored. EXAMPLES >> r2=constrain(r,'TPr(banana)',0.8) >> r2=constrain(r,'TPr(banana)',0.8,'error(fruit)',0.3) Multiple constrains in a matrix: >> load fruit; [tr,ts]=randsubset(a,0.5); >> p=sdgauss(tr) >> r=sdroc(ts,p,'confmat') >> Q=NaN*ones(3); Q(3,2)=0.2; Q(1,1)=0.95; Q(2,2)=0.6 >> r2=constrain(r,'nconfmat',Q)