Taking the textual analysis technique as an example, Koppel and Shtrimberg (2006) found that the classification accuracy of machine learning algorithms can reach 70.3 and 65.9% for intra-sample and out-of-sample classifications, respectively.
Specifically, all detected metabolites were used as input variables, and principal components were ranked on significant differences between scores of sample classifications.
The subtype classifications of TCGA GBM samples according to either Phillips et al. or Verhaak et al. have been reported in summary (Huse et al., 2011 [37]) and individual sample classifications were kindly provided by Dr. Cameron Brennan.
In GSEA, a gene's rank is determined by its correlation with the experimental sample classifications.
Despite this limitation, we had sufficient power to detect statistically significant differences in arsenic species across sample classifications.
The new small sample classification algorithm is worthy of further promotion.
Automatic classification was successful for all but four samples out of 14,400 classification trial configurations, representing 403,200 sample classification attempts (28 attempts per configuration).
These results shows that the first discriminant function is the most important in honey sample classification.
Variables with a larger VIP are more relevant for sample classification.
Our evaluation metrics were: (1) accuracy of out-of-sample classification and (2) reproducibility of spatial maps.
