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Table 8 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

0.270

(0.134)

0.288

(0.140)

0.499

(0.118)

0.475

(0.102)

GY-2

0.322

(0.118)

0.307

(0.111)

0.538

(0.117)

0.567

(0.116)

GY-3

0.310

(0.138)

0.268

(0.108)

0.452

(0.117)

0.453

(0.118)

GY-4

0.319

(0.121)

0.325

(0.118)

0.482

(0.112)

0.518

(0.115)

GY-5

0.333

(0.161)

0.326

(0.142)

0.545

(0.104)

0.550

(0.107)

GY-6

0.562

(0.159)

0.561

(0.157)

0.668

(0.087)

0.701

(0.083)

GY-7

0.263

(0.124)

0.290

(0.117)

0.503

(0.117)

0.529

(0.115)

Lower class

DTH-1

0.370

(0.114)

0.414

(0.124)

0.629

(0.091)

0.630

(0.091)

DTH-2

0.417

(0.134)

0.429

(0.132)

0.548

(0.116)

0.521

(0.104)

DTH-3

0.506

(0.158)

0.511

(0.151)

0.641

(0.093)

0.650

(0.095)

DTH-4

0.292

(0.090)

0.298

(0.089)

0.350

(0.094)

0.363

(0.097)

DTH-5

0.355

(0.158)

0.384

(0.164)

0.551

(0.091)

0.546

(0.087)

DTH-6

0.444

(0.087)

0.467

(0.094)

0.530

(0.119)

0.520

(0.112)

DTH-7

0.462

(0.116)

0.482

(0.113)

0.580

(0.122)

0.591

(0.115)

DTH-8

0.387

(0.104)

0.382

(0.103)

0.603

(0.089)

0.599

(0.095)

DTH-9

0.376

(0.138)

0.367

(0.112)

0.532

(0.105)

0.535

(0.107)

DTH-10

0.557

(0.112)

0.553

(0.114)

0.575

(0.117)

0.578

(0.124)

  1. Mean values of the area under the precision-recall curve AUCpr (standard deviation in parentheses) of 50 random partitions for the 15 and 30 % upper classes for grain yield (GY) in 7 environments (1–7) and for 15 and 30 % lower classes for days to heading (DTH) for classifier PNN with two and three classes. Numbers in bold are the highest AUCpr values