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(a) Ionosphere, (b) Letter, (c) Pendigits, (d) Pima-Indians, (e) WDBC, and (f) Wine.
Table 3 compares the predictive performance among the CDSS models designed based on our proposed methods and the one-sided selection methods using the WDBC dataset.
The relationship between the parameter and the recognition rate of our method on WDBC dataset of a single run is shown in Figure 6, which shows that our method obtains good performance in a large range; well-performed recognition rates do not vary much with the change of the value of [gamma].
In Tables 1, 2, and 3, we show the results obtained for the WDBC dataset with 30 dimensions and 2 clusters with 569 samples; this dataset was tested with 2 to 10 clusters with the IT2FPCM and IT2FCM algorithms using different validation indices to evaluate the performance of both algorithms.
He brings more than 25 years of industry-related experience to his new role as WDBC president.
Data set attribute example class Breast-Cancer (BC) 9 683 2 Credit-screening (CS) 15 690 2 Diabetes (DIAB) 8 768 2 Iris (IR) 4 150 3 Letter-recognition (LR) 16 20000 26 Vowel(VO) 10 528 11 Wdbc 10 569 2 Wine 13 768 3 Wpbc 33 194 2 Zoo 16 101 7 Table 2: Model error comparison of bilinear grid search with other search methods.
The experiments are, respectively, conducted on 6 data sets in UCI machine learning repository, including "Iris," "Wine," "WDBC," "Seeds," "Sonar," and "Ionosphere." These data sets are with normal dimension and number of instances.
Estadisticas del numero de generaciones empleadas para lograr una TEC del 10% con WDBC. AGS AGIFCM (m=2) AGIFCM (m=3) AGIFCM (m=5) Numero de Reglas Media DE Media DE Media DE Media DE 2 281.4 354.64 11.4 22.44 3 2.74 8 17.96 4 37.3 39.85 7.6 16.19 2.1 1.19 2 1.41 6 123.4 122.28 2.3 1.05 9.1 21.41 1.9 0.73 8 39.1 60.75 5.6 9.24 2.7 1.33 3.5 6.53 Tabla 3.
WDBC committee member Cedric Moon said, "In other words, subtitling for deaf viewers should be excluded from the copyright laws."
The datasets of Parkinson and Wisconsin diagnostic breast cancer (WDBC) publicly available from the UCI machine learning data repository were used.
For further verification of the effectiveness of the proposed algorithm, five real-world datasets from UCI Machine Learning Repository [34] (i.e., Iris, Abalone, Wine, Ecoli, and Breast Cancer Wisconsin (WDBC)) are employed to test the performance of the proposed algorithm against LOF, KNN, SVDD, and EODSP.