Arabic Sentiment Classification Using Convolutional Neural Network and Differential Evolution Algorithm

Table 4

The results based on 5-fold CV accuracy as fitness function value used with DE/best/2, different population sizes, and mutation parameter.

DE parameters	DE/best/2--				DE/best/2--
Population size	5		10		5		10
Dataset	Accuracy	Time (s)	Accuracy	Time (s)	Accuracy	Time (s)	Accuracy	Time (s)
ArTwitter	91.48	16570.82	91.27	21842.62	91.37	12498.83	91.73	20115.25
STD	86.63	4160.50	87.03	8306.28	86.75	5956.65	86.75	9726.51
AAQ	85.54	14978.24	86.76	68793.32	83.86	22016.83	85.91	76816.73
ASTD-B	80.85	4408.58	81.48	8175.77	81.04	4455.77	82.05	9056.05
AJGT	91.06	6314.36	92.56	8543.75	92.06	3259.03	91.67	21229.50
Average	87.11	9286.5	87.82	23132.35	87.01	9637.42	87.62	27388.81