GitHub - bocheng97/TRGN510_Final: FIrst_taste_of_Machine_learning_in_R

In this project, I try to use a machine learning package, MLSeq from Bioconductor to find out the best model that predicts breast cancer subtype. I use 28 data sets from TCGA to train and test this model using 12 datasets. So I may do many copy and paste, but I will give my understanding and opinions in the R notebook. According to the Vignette, I've input the data and converted the data to be right data frames which are ready to do MLSeq. And the next step is to choose a model, do the Normalization and transformation, and use the normalized data to train model.