weka klasteryzacja

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Preprocess | Classify Cluster Assodate | Sełect attributes | Visualize

Clusterer

Choose SimpleKMeans -N 6 -A "weka.core.EudideanDistance -R first-last" -I 500 -S 10

Cluster modę o Use training set

Supplied test set Percentage split Classes to dusters evaluation

Clusterer output

Set...

% 66

(Num) P

=== Run information ===

Scheme:weka.clusterers.SimpleKMeans -N 6 -A "weka.core.EuclideanDistance -R first-last" -I 500 -S 10 Relation:    BreastTissue

Instances:    106

Attributes:

Storę dusters for visualization

Ignore attributes

Start

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Result list (right-dick for options)

18:40:16- SimpleKMeans

18:47:26 - SimpleKMeans

9

10

PA500

HFS

DA

Area

A/DA

MaxIP

DR

P

Te3t mode:evaluate on training data === Model and evaluation on training set

kMeans

Number of iterations: 8

Within cluster sum of sguared errors: 8.203036402785267 Missing values globally replaced with mean/mcde

Cluster centroid3:

Cluster#

Attribute	Fuli Data (106)	0 (31)	1 (7)	2 (9)	3 (8)	4 (23)	5 (28)
10	784.2516	246.6125	453.4986	333.2922	2397.48	1699.9904	393.998
PA500	0.1201	0.1535	0.2656	0.2114	0.1018	0.0651	0.068
HFS	0.1147	0.11	0.1753	0.3041	0.2212	0.0724	0.0482
DA	190.5686	64.0161	228.1187	145.1658	606.4418	350.1169	86.0082
Area	7335.1552	1231.6419	9396.0529	4183.218	51567.6707	8792.0293	755.9348
A/DA	23.4738	14.3606	41.3445	26.4969	76.5423	28.8563	8.5401
MaxIP	75.3813	35.995	73.9217	60.5068	299.8219	117.5609	25.3599
DR	166.7106	50.274	215.6	127.4646	491.6229	315.8757	80.6544
P	810.6381	282.6999	551.6648	427.9985	2531.0712	1662.9603	391.2018

Time taken to build model {fuli training data) : 0.02 seconds === Model and evaluation on training set ===

Clustered Instances

Weka Clusterer Visualize: 18:47:26 - SimpleKMeans (BreastTissue)

(H)

Status

OK

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