Instance Selection Methods Comparison

# 02/11/2009 02:11

Test description:

Crosvalidation test 10x10
Normalization [-1,1]
Vector Selection
Classification=kNN k=1 Metric=Euclidean

Appendicitis	Breast C.W.	Heart	Diabetes	Iris	Wine
acc.	std.	com.	sdt.	acc.	std.	com.	sdt.	acc.	std.	com.	sdt.	acc.	std.	com.	sdt.	acc.	std.	com.	sdt.	acc.	std.	com.	sdt.
CNN	75.3	13.2	36.9	3.5	89.4	3.8	11.6	1.0	69.9	8.3	43.5	2.3	63.4	4.9	50.5	1.4	89.7	7.9	15.9	2.0	89.5	7.1	15.5	2.3
DROP1	NaN	0.0	NaN	0.0	NaN	0.0	NaN	0.0	NaN	0.0	NaN	0.0	64.3	6.1	6.1	1.5	89.9	8.9	7.3	1.3	88.2	10.0	5.8	1.0
DROP2	83.4	10.9	8.5	1.8	94.5	3.1	2.9	0.7	76.3	8.3	12.0	2.5	68.1	5.0	17.8	1.8	92.1	8.2	10.1	1.6	92.2	6.1	11.3	1.5
DROP3	84.8	10.3	7.5	1.1	95.4	2.5	2.6	0.5	78.7	7.7	11.4	1.9	71.2	4.7	12.3	1.5	92.9	7.4	9.7	1.4	92.6	6.3	11.8	1.6
DROP5	82.7	11.9	8.5	1.8	94.5	2.8	3.0	0.7	77.1	8.3	12.2	2.5	68.3	5.7	17.9	2.1	92.8	7.6	10.1	1.6	92.5	6.2	11.3	1.5
ENRBF	84.1	10.2	5.1	1.4	89.9	9.1	1.8	0.4	68.7	9.3	7.2	1.4	72.8	5.0	11.1	0.9	93.9	6.5	12.4	1.6	89.5	7.8	12.3	2.0
ENN	83.9	10.4	92.6	1.2	96.3	1.9	97.6	0.3	77.1	8.2	89.5	1.1	73.8	4.5	85.7	0.7	95.1	5.3	96.6	0.4	95.2	5.1	97.2	0.6
RENN	83.9	10.4	92.1	1.3	96.3	1.9	97.5	0.3	77.0	8.2	88.2	1.4	73.9	4.4	83.8	0.9	95.3	5.3	96.0	0.6	95.2	5.1	97.2	0.6
ICF	81.6	10.8	20.4	5.0	94.0	2.9	3.8	0.7	74.4	8.7	24.5	2.3	69.9	5.6	23.3	1.0	92.9	7.2	29.8	4.4	91.5	6.8	13.2	2.0
GE	81.6	10.4	55.0	3.5	94.2	2.5	37.0	1.8	76.0	7.8	98.5	0.7	69.9	4.4	94.6	0.6	94.7	5.3	32.1	2.0	95.3	4.9	83.9	1.9
RNGE	79.5	11.1	37.3	3.4	90.9	3.2	12.1	0.9	74.3	7.7	51.8	2.0	66.0	4.7	60.0	1.1	89.4	7.4	15.2	1.7	91.1	6.5	21.6	1.7
RMHC	84.8	10.2	2.1	0.0	96.2	2.3	0.3	0.0	81.9	6.8	0.8	0.0	73.6	4.4	0.3	0.0	92.1	7.7	2.2	0.0	91.3	6.9	1.9	0.0
MC	84.7	10.0	2.1	0.0	96.3	2.4	0.3	0.0	81.1	8.4	0.8	0.0	73.0	5.1	0.3	0.0	92.1	7.7	2.2	0.0	90.1	9.1	1.9	0.0

CNN Configuration:

Classifier=kNN k=3, Metric=Intemi.Metric.SquareEuclidean

DROP1 Configuration:

Classifier=kNN k=3, Metric=Intemi.Metric.SquareEuclidean
Order=Random
ENN=False
IncludePruned=False

DROP2 Configuration:

Classifier=kNN k=3, Metric=Intemi.Metric.SquareEuclidean
Order=EnemyDistance
ENN=False
IncludePruned=True

DROP3 Configuration:

Classifier=kNN k=3, Metric=Intemi.Metric.SquareEuclidean
Order=EnemyDistance
ENN=True
IncludePruned=True

DROP5 Configuration:

Classifier=kNN k=3, Metric=Intemi.Metric.SquareEuclidean
Order=EnemyDistanceAndReverse
ENN=False
IncludePruned=True

ENRBF Configuration:

Sigma=0.5
Strenght=0.05
RemoveNoise=True
Tolerance=0.95
Metric=Intemi.Metric.SquareEuclidean

ENN Configuration:

Classifier=kNN k=3, Metric=Intemi.Metric.SquareEuclidean

RENN Configuration:

Classifier=kNN k=3, Metric=Intemi.Metric.SquareEuclidean

ICF Configuration:

Metric=Intemi.Metric.SquareEuclidean
Filter=(ENN using kNN k=3)

GE Configuration:

Metric=Intemi.Metric.SquareEuclidean
MeighboursType=Gabriel

RNGE Configuration:

Metric=Intemi.Metric.SquareEuclidean
MeighboursType=Relative

RMHC Configuration:

Classifier=kNN k=1, Metric=Intemi.Metric.SquareEuclidean
Search=randomMutation
Mutations=1000

MC Configuration:

Classifier=kNN k=1, Metric=Intemi.Metric.SquareEuclidean
Search=monteCarlo
Mutations=1000