hi knimers
i want to implement manual sampling approach it's name is Balanced Stratified Sampling
Balanced stratified sampling is selecting the samples from m strata, but of equal size. If there are minority
or majority classes then over-sampling or under-sampling respectively need to be performed as
required based on the distribution of the classes.
the first option of balancing is through ignoring the minority classes for the ratios above 1:100. As the response variable is of multivariate in nature, ignoring the minority class leads to minimal error.
The second method adopted is to take equal size of samples from each strata by reducing the stratum to p<m, such that p changing as the size of the sub-sample changes gradually from 500 to 30000.
The balancing criteria has been maintained in an excel file with the required size(i.e from 500–
30000) and that file has been given as input for the already built-in stratified model.
anyone can help me???
thank you very much