Supervised DNA Barcodes species classification: analysis, comparisons and results

Table 5 Accuracies for the empirical datasets [%]

Dataset	SVM	Jrip	J48	Naïve Bayes	Average	Standard deviation
Cypraeidae	94.32	86.93	91.76	93.18	91.55	2.82
Drosophila	98.28	94.83	91.38	96.55	95.26	2.55
Inga	89.83	88.14	88.14	91.53	89.41	1.41
Bats	100.00	100.00	98.15	100.00	99.54	0.80
Fishes	95.50	90.09	92.79	97.30	93.92	2.73
Birds	98.42	84.86	91.80	94.32	92.35	4.93
Fungi	80.00	50.00	60.00	70.00	65.00	11.20
Algae	100.00	60.00	60.00	100.00	80.00	20.00

Results of the Weka supervised learning methods tested on empirical datasets show that SVM and Naïve Bayes outperform the other techniques in term of percentage of the correct species identification. The differences between SVM and the other algorithms result statistically significant (p-value ≤ 0.001), except for Naive Bayes (p-value > 0.05). The best performances are highlighted in bold for each dataset.

ISSN: 1756-0381