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Table 7 Wheat datasets

From: Genome-enabled prediction using probabilistic neural network classifiers

  PNN15% (two classes) PNN15% (three classes) PNN30% (two classes) PNN30% (three classes)
Upper class
GY-1 0.658 (0.140) 0.675 (0.135) 0.708 (0.082) 0.735 (0.085)
GY-2 0.691 (0.091) 0.713 (0.100) 0.765 (0.081) 0.805 (0.076)
GY-3 0.694 (0.123) 0.697 (0.120) 0.664 (0.115) 0.663 (0.115)
GY-4 0.674 (0.120) 0.693 (0.105) 0.701 (0.112) 0.748 (0.107)
GY-5 0.710 (0.123) 0.727 (0.115) 0.775 (0.083) 0.782 (0.089)
GY-6 0.880 (0.097) 0.878 (0.100) 0.830 (0.075) 0.864 (0.070)
GY-7 0.649 (0.160) 0.690 (0.158) 0.708 (0.116) 0.736 (0.106)
Lower class
DTH-1 0.724 (0.112) 0.779 (0.109) 0.791 (0.074) 0.791 (0.072)
DTH-2 0.773 (0.094) 0.789 (0.090) 0.763 (0.100) 0.751 (0.092)
DTH-3 0.840 (0.100) 0.843 (0.101) 0.802 (0.074) 0.806 (0.074)
DTH-4 0.584 (0.098) 0.585 (0.097) 0.568 (0.094) 0.587 (0.102)
DTH-5 0.763 (0.121) 0.779 (0.128) 0.754 (0.075) 0.756 (0.072)
DTH-6 0.708 (0.086) 0.736 (0.085) 0.722 (0.097) 0.722 (0.098)
DTH-7 0.765 (0.096) 0.775 (0.095) 0.775 (0.097) 0.785 (0.088)
DTH-8 0.750 (0.080) 0.755 (0.082) 0.803 (0.065) 0.799 (0.067)
DTH-9 0.764 (0.105) 0.774 (0.090) 0.736 (0.088) 0.743 (0.087)
DTH-10 0.763 (0.763) 0.768 (0.098) 0.774 (0.094) 0.787 (0.102)
  1. Mean values of the area under the ROC curve AUC (standard deviation in parentheses) of 50 random partitions for the 15 and 30 % upper class for grain yield (GY) in 7 environments (1–7) and for 15 and 30 % lower class for days to heading (DTH) for classifier PNN with two and three classes. Numbers in bold are the highest AUC values