Cluster analysis
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การวิเคราะห์กลุ่ม ( Cluster Analysis ). โดย นางสาวจิตรลดา ทองอันตัง นายสุขสมพร อโนไท. 1.ความหมายของ Cluster Analysis

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การวิเคราะห์กลุ่ม ( Cluster Analysis )

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Cluster analysis

(Cluster Analysis)


Cluster analysis

1. Cluster Analysis

  • Case ( ) 2 Case Case

    -


Cluster analysis

Inter-cluster distances are maximized

Intra-cluster distances are minimized

Cluster Analysis

(Minimize Intra-Cluster Distances) (Maximize Inter-Cluster Distances)


Cluster analysis1

Cluster Analysis

  • (Cases) (Objects) (Similarity) (Dissimilarity or Distance) (Variables)

  • (Cluster)


Cluster analysis

2.

  • 1 2


3 cluster analysis

3. Cluster Analysis

Case


Cluster analysis

1


Cluster analysis

2 1 Case 1


Cluster analysis

1 Case Case


Cluster analysis

4. (Similarity Measure)

Cluster Case Case Case Case


Cluster analysis

4.1 2 2 2 2 2 ( )


Cluster analysis

(Euclidean Distance)


Cluster analysis

3

  • ==400+90,000=90,400


Cluster analysis


Cluster analysis


Cluster analysis

=

50


Cluster analysis

4.3 (Binary data)

2 2 2 2

4 1 0 4 (X1, X2 , X3 , X4)


Cluster analysis

  • X2 X3 X1 X4


Cluster analysis

X A1=


Cluster analysis

  • p (X1, X2 , Xp) i j


Cluster analysis

4.4

1. (Square Euclidean Distance)

2. (Euclidean Distance)


Cluster analysis

4.5

  • Simple Matching


Cluster analysis

5 6 1


Cluster analysis

2


Cluster analysis

5. Cluster Analysis

Cluster Analysis 2

  • Hierarchical Cluster Analysis

  • K-Means Cluster Analysis


Cluster analysis

5.1 Hierarchical Cluster Analysis

Case

1. Case Case ( Case 200 200 K-Means Cluster )

2.

3. Case


Cluster analysis

6. (Hierarchical Cluster Aalysis)

(Hierarchical Cluster Aalysis) 3 3 1 2 ( 3 )


Cluster analysis

6.1 Hierarchical Cluster Analysis

2

1. Agglomerative Hierarchical Cluster Analysis

2. Divisive Hierarchical Cluster Analysis

Agglomerative Hierarchical Cluster Analysis


Cluster analysis

6.1.1 Agglomerative HierarchicalCluster Analysis

n item n-1 n 1 1 n


Cluster analysis

Agglomerative Hierarchical Cluster Analysis

Agglomerative Hierarchical Cluster Analysis case = cluster n case = n cluster cluster 1 2 cluster cluster 1 n n = 1,000 999 1,000 cluster 999 cluster , 998 cluster 1 cluster case 200 case Hierarchical Cluster


Cluster analysis

Agglomerative Hierarchical Cluster Analysis Linkage method 3

1.single linkage ( nearest neighbor) 2. complete linkage ( furthest neighbor)

3.average linkage ( average distance) 3


Cluster analysis

Hierarchical Cluster 3

1. (Interval scale) (Ratio scale)

2. (Count Data)

3. Binary 2 0 1


Cluster analysis

Case Case Cluster 3 (Interval scale , Count Data , Binary )


Cluster analysis

Case

Case Case


Cluster analysis


Cluster analysis

  • 1. Between groups Linkage Average Linkage Between Groups UPGMA (Unweightede Pair-Group Method Using Arithmetic Average)


Cluster analysis

  • Case Case Cluster i Case Cluster j

    Cluster i Cluster j Cluster Cluster i j Cluster


Cluster analysis

2. Within-group Linkage Technique

Cluster Case Cluster


Cluster analysis

3. Nearest Neighbor Single Linkage

  • Cluster 2 Cluster dik Cluster i k Cluster i j dij < dik


Cluster analysis

4. Furthest Neighbor Technique Complete Linkage

Cluster 2 Cluster

dik = Cluster i k

dij = Cluste i j

dij < dik Cluster i j Cluster


Cluster analysis

5. Centroid Clustering

  • Centroid Cluster Cluster Centroid Cluster Case Centroid Centroid Cluster Cluster Cluster


Cluster analysis

6. Median Clustering

Cluster 2 Cluster Cluster () Centroid Clustering Cluster Cluster () Median Clustering Median Centroid Median Clustering Median Centroid Median Cluster Cluster


Cluster analysis

7. Wards Method

Sum of the squared within-cluster distance Cluster Sum of square within-cluster distance Square within-cluster distance Square Euclidean distance Case Cluster Mean


Cluster analysis

8.

  • Cluster

    1) Dendogram Dendogram Cluster Cluster

    2)Multidimension Scaling

    3) Discriminant


Cluster analysis

6.1.2 Divisive Hierarchical Cluster Analysis

item n 2 3 n 1


Cluster analysis

9. (Nonhierarchical Cluster Analysis K Means Cluster Analysis )

  • k K-Means Clustering


Cluster analysis

1. K

2. Centroid () Centroid 1. 1.

3. 2.


Cluster analysis

9.1 K-Means Clustering

Case Case Cluster k K-Means (Iteration) Cases Case


Cluster analysis

9.2 K-Means Clustering

K-Means Clustering

(Interval Scale) (Ratio Scale) Binary Hierarchical


Cluster analysis

9.3 K-Means 4

1 k

-

-

  • 2 C

  • 3 2


Cluster analysis

1

2 ESSZ(Error Sum Square)


Cluster analysis

4 3

4 4 2


Cluster analysis

9.4 Hierarchical K-Means

1. K-Means Case n 200 n K-Means Hierarchical Case Hierarchical


Cluster analysis

2. K-Means

  • K-Means

    3, 4 5

  • Hierarchical

    K-Means


Cluster analysis

3. Hierarchical Standardized K-Means Standardized

4. K-Means Euclidean Distance

  • Hierarchical


Cluster analysis

Cluster Analysis Discriminant Analysis

  • Cluster Analysis

    1.

    2. Case

    3.

    DiscriminantAnalysis

    1.

    2. Case .

    3.


Cluster analysis

Hierarchical Cluster

5 2550

1. 2550

2. 2550

3. 2550

4. 2550

5. 2550


Cluster analysis

2020 calories,sodium,alcohol,cost


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