Complexity

Research Article

[Retracted] Predicting Course Grade through Comprehensive Modelling of Students’ Learning Behavioral Pattern

Table 4

Performance measure of classification methods for course “digital writing skills” with different feature numbers.


Features	Methods	Accuracy	Precision	F1	Recall	Jaccard	Fbeta

12	NN	0.8956	0.5685	0.5856	0.6067	0.5685	0.5750
	L-SVM	0.8956	0.5775	0.5977	0.6233	0.5775	0.5851
	R-SVM	0.8901	0.5766	0.5947	0.6193	0.5726	0.5832
	GP	0.8787	0.5712	0.5856	0.6050	0.5712	0.5766
	DT	0.9889	0.9333	0.9360	0.9400	0.9333	0.9343
	RF	0.8956	0.5775	0.5977	0.6233	0.5775	0.5851
	NeuralN	0.8956	0.5807	0.5996	0.6233	0.5807	0.5878
	AB	0.9564	0.7783	0.7938	0.8350	0.7783	0.7833
	NB	0.7681	0.5408	0.5278	0.5404	0.4903	0.5332

15	NN	0.8956	0.5692	0.5859	0.6067	0.5692	0.5755
	L-SVM	0.8956	0.5775	0.5977	0.6233	0.5775	0.5851
	R-SVM	0.8956	0.5775	0.5977	0.6233	0.5775	0.5851
	GP	0.8678	0.5051	0.5237	0.5467	0.5051	0.5121
	DT	0.9889	0.9267	0.9267	0.9267	0.9267	0.9267
	RF	0.8956	0.5787	0.5985	0.6233	0.5787	0.5861
	NeuralN	0.8956	0.5807	0.5996	0.6233	0.5807	0.5878
	AB	0.9564	0.7783	0.7938	0.8350	0.7783	0.7833
	NB	0.6026	0.5144	0.4197	0.4291	0.3668	0.4528

18	NN	0.8956	0.5712	0.5899	0.6133	0.5712	0.5782
	L-SVM	0.8956	0.5775	0.5977	0.6233	0.5775	0.5851
	R-SVM	0.8845	0.5745	0.5920	0.6168	0.5680	0.5808
	GP	0.8678	0.5273	0.5547	0.5900	0.5273	0.5375
	DT	0.9889	0.9333	0.9360	0.9400	0.9333	0.9343
	RF	0.8956	0.5787	0.5985	0.6233	0.5787	0.5861
	NeuralN	0.8956	0.5821	0.6005	0.6233	0.5821	0.5890
	AB	0.9564	0.7783	0.7938	0.8350	0.7783	0.7833
	NB	0.5971	0.5189	0.4269	0.4294	0.3735	0.4597

21	NN	0.8956	0.5787	0.5985	0.6233	0.5787	0.5861
	L-SVM	0.8956	0.5775	0.5977	0.6233	0.5775	0.5851
	R-SVM	0.8845	0.5745	0.5920	0.6168	0.5680	0.5808
	GP	0.8678	0.5264	0.5545	0.5900	0.5264	0.5369
	DT	0.9889	0.9333	0.9360	0.9400	0.9333	0.9343
	RF	0.8956	0.5775	0.5977	0.6233	0.5775	0.5851
	NeuralN	0.8956	0.5821	0.6005	0.6233	0.5821	0.5890
	AB	0.9564	0.7783	0.7938	0.8350	0.7783	0.7833
	NB	0.5974	0.5185	0.4238	0.4279	0.3698	0.4576

NN denotes Nearest Neighbors, L-SVM stands for Linear SVM, R-SVM denotes RBF SVM, GP stands for Gaussian Process, DT denotes Decision Tree, RF stands for Random Forest, NeuralN stands for Neural Networks, AB denotes AdaBoost, and NB stands for Naive Bayes.