Journal of Biological Engineering

Table 6 Results summary for the leukemia dataset

From: RN-Autoencoder: Reduced Noise Autoencoder for classifying imbalanced cancer genomic data

Dataset: leukemia
Classifier	Metrics
Classifier	Model	Test Acc	Precision	Recall	F1	Kappa	MCC	GM
SVM-RBF	Original	0.6765	1	0.2143	0.3529	0.2429	0.3718	0.4629
	RN-SMOTE	0.6765	1	0.2143	0.3529	0.2429	0.3718	0.4629
	Extracted	0.7647	1	0.4286	0.6	0.4688	0.5533	0.6547
	RN-Extracted	0.9118	1	0.7857	0.88	0.8118	0.8266	0.8864
SGD (LR)	Original	0.6765	1	0.2143	0.3529	0.2429	0.3718	0.4629
	RN-SMOTE	0.7353	1	0.3571	0.5263	0.3953	0.4963	0.5976
	Extracted	0.7941	1	0.5	0.6667	0.5405	0.6086	0.7071
	RN-Extracted	0.8824	1	0.7143	0.8333	0.7463	0.7715	0.8452
KNN	Original	0.7059	0.8333	0.3571	0.5	0.3359	0.3965	0.5825
	RN-SMOTE	0.7647	0.7143	0.7143	0.7143	0.5143	0.5143	0.7559
	Extracted	0.7647	1	0.4286	0.6	0.4688	0.5533	0.6547
	RN-Extracted	0.7941	0.8889	0.5714	0.6957	0.5509	0.5817	0.7368
LDA	Original	0.7059	1	0.2857	0.4444	0.32	0.4364	0.5345
	RN-SMOTE	0.8235	0.75	0.8571	0.8	0.6434	0.648	0.8281
	Extracted	0.7941	0.8182	0.6429	0.72	0.5609	0.5711	0.7606
	RN-Extracted	1	1	1	1	1	1	1

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