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Table 6 IMPROVEMENT of location normalization methods. IMPROVEMENT is defined (in the Results) based on improvement of LOOCV classification error rate of a given normalization method over that of N ONRM. The methods are arranged in the same order as those in Table 5. For a given data set, the biggest IMPROVEMENT(s) is shown in bold. The methods and data sets are described in Tables 1, 2 and 4, respectively.

From: Evaluation of normalization methods for cDNA microarray data by k-NN classification

Location Normalization method IMPROVEMENT (%, LIVER CANCER) IMPROVEMENT (%, LYMPHOMA) IMPROVEMENT (%, RENAL CELL CARCINOMA) IMPROVEMENT (%, GASTRIC CARCINOMA) IMPROVEMENT (%, LUNG CANCER) IMPROVEMENT RANGE (%)
N ONRM 0 0 0 0 0 0 - 0
GMEDIAN 19 7 33 22 5 5 – 33
SL LOESS 33 -2 44 56 3 -2 – 56
SL FILTERW3 23 19 44 45 0 0 – 45
SL FILTERW7 29 5 44 34 9 5 – 44
IG LOESS 34 30 44 33 5 5 – 44
IL LOESS 46 42 44 33 23 23 – 46
IST SPLINE 36 33 52 56 7 7 – 56
IG SG LOESS 33 51 44 100 21 21 – 100
IG LOESS-SL LOESS 44 56 50 56 33 33 – 56
IL LOESS-SL LOESS 48 58 44 44 26 26 – 58
IG LOESS-SL FILTERW3 22 49 61 33 33 22 – 61
IG LOESS-SL FILTERW7 44 58 50 56 40 40 – 58
IST SPLINE-SL LOESS 40 62 50 33 47 33 – 62
IST SPLINE-SL FILTERW3 22 48 61 34 42 22 – 61
IIST SPLINE-SL FILTERW7 42 52 44 34 42 34 – 52
Q SPLINEG 22 28 59 100 23 22 – 100
QS PLINER 18 54 59 100 23 18 – 100
Q SPLINEG-SL LOESS 32 26 50 78 37 26 – 78
Q SPLINEG-SL FILTERW3 29 30 27 78 12 12 – 78
Q SPLINEG-SL FILTERW7 26 28 55 78 37 26 – 78
QS PLINER-SL LOESS 23 61 56 78 37 23 – 78
QS PLINER-SL FILTERW3 23 58 39 78 9 9 – 78
QS PLINER-SL FILTERW7 16 56 50 67 23 16 – 67