Wage Gender Gap – Distribution and Log Values. PUDS Quiz 2.

We did some machine learning with standard random forest classifier on the study genes and then on genes specific to relationships we saw in the data analysis of groups and subgroups of genes. Not all subsets were done, but some were terrible and some just not good at all. The best performer was the genes from the study. The avg/median of groups and subgroups didn't seem to work very well. The best score was 70% with genes of study and 60% with some genes that seemed to be more associated with males. It seems that the 4 class model on the proposed 4 classes scored 30% with the genes in the study and 40% in the male gene predictor in the male inclusive samples. The transition state seems likely but at times it misidentified an mDLBCL class as it for IFNG-L when it should be CHL or pDLBCL. It's apparent that the large B-cell lymphomas are EBV associated and so is CHL but they remain difficult to classify even with a classifier tool.

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