Building gene expression profile classifiers with a simple and efficient rejection option in R

Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco; Savino, Alessandro; Hafeezurrehman, Hafeez

doi:10.1186/1471-2105-12-S13-S3

BMC Bioinformatics

Table 2 Classification performances

From: Building gene expression profile classifiers with a simple and efficient rejection option in R

	G ₃				G ₄				G ₅				G ₆
Classifier	Sens	CI	Spec	CI	Sens	CI	Spec	CI	Sens	CI	Spec	CI	Sens	CI	Spec	CI
K-NN + rule	0.70	[0.61-0.79]	0.42	[0.31-0.53]	0.70	[0.65-0.75]	0.45	[0.36-0.55]	0.59	[0.49-0.69]	0.42	[0.35-0.49]	0.55	[0.49-0.62]	0.59	[0.48-0.70]
RF + rule	0.61	[0.53-0.69]	0.76	[0.69-0.83]	0.75	[0.71-0.79]	0.68	[0.60-0.77]	0.69	[0.66-0.73]	0.78	[0.70-0.86]	0.77	[0.70-0.84]	0.63	[0.53-0.73]
N-NET+rule	0.38	[0.23-0.53]	0.68	[0.53-0.83]	0.80	[0.70-0.90]	0.50	[0.43-0.57]	0.57	[0.51-0.63]	0.71	[0.59-0.84]	0.81	[0.75-0.87]	0.34	[0.25-0.44]
K-NN-OC_SOCMT	0.74	[0.67-0.82]	0.20	[0.17-0.23]	0.90	[0.87-0.93]	0.29	[0.23-0.35]	0.91	[0.89-0.92]	0.23	[0.21-0.25]	0.86	[0.81-0.90]	0.16	[0.10-0.21]
KMeans-OG_SOCM	0.47	[0.41-0.53]	0.66	[0.60-0.73]	0.54	[0.50-0.57]	0.69	[0.62-0.76]	0.65	[0.61-0.70]	0.67	[0.63-0.71]	0.61	[0.53-0.69]	0.50	[0.38-0.62]
PCA-OC_SOCMT	0.40	[0.35-0.45]	0.79	[0.77-0.81]	0.36	[0.31-0.42]	0.77	[0.69-0.84]	0.29	[0.25-0.34]	0.76	[0.69-0.82]	0.29	[0.23-0.35]	0.79	[0.72-0.86]
Parzen-OC_SOCMT	0.44	[0.39-0.50]	0.70	[0.64-0.76]	0.49	[0.46-0.52]	0.73	[0.67-0.79]	0.51	[0.47-0.54]	0.77	[0.70-0.83]	0.49	[0.45-0.52]	0.79	[0.70-0.87]
SVM-OC_SOCMT	0.20	[0.16-0.24]	0.72	[0.68-0.77]	0.22	[0.20-0.25]	0.76	[0.70-0.81]	0.27	[0.24-0.30]	0.77	[0.70-0.83]	0.28	[0.25-0.31]	0.80	[0.72-0.88]
s K-NN-OC_MOCV	0.99	[0.98-1.00]	0.01	[0.00-0.02]	1.00	[1.00-1.00]	0.00	[0.00-0.00]	1.00	[1.00-1.00]	0.00	[0.00-0.00]	1.00	[1.00-1.00]	0.00	[0.00-0.00]
KMeans-OC_MOCV	0.36	[0.29-0.43]	0.71	[0.63-0.80]	0.48	[0.43-0.54]	0.78	[0.72-0.83]	0.59	[0.57-0.61]	0.69	[0.64-0.73]	0.46	[0.44-0.49]	0.68	[0.60-0.77]
PCA-OC_MOCV	0.42	[0.36-0.48]	0.71	[0.65-0.77]	0.50	[0.48-0.52]	0.78	[0.72-0.83]	0.49	[0.46-0.53]	0.77	[0.70-0.83]	0.43	[0.40-0.45]	0.70	[0.60-0.80]
Parzen-OC_MOCV	0.36	[0.31-0.40]	0.70	[0.64-0.76]	0.34	[0.28-0.41]	0.78	[0.72-0.83]	0.32	[0.28-0.36]	0.77	[0.70-0.83]	0.22	[0.20-0.24]	0.70	[0.60-0.80]
SVM-OC_MOCV	0.19	[0.15-0.23]	0.76	[0.74-0.79]	0.25	[0.22-0.28]	0.79	[0.73-0.85]	0.27	[0.24-0.30]	0.78	[0.72-0.84]	0.22	[0.20-0.24]	0.72	[0.63-0.81]

For each group of experiments results are provided in terms of average sensitivity (Sens) and specificity (Spec) with the related Confidence Intervals (CI). Confidence intervals are computed with 95% LOC.

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