MIS 451 Building Business Intelligence Systems Demo on Classification and Clustering.
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Transcript of MIS 451 Building Business Intelligence Systems Demo on Classification and Clustering.
![Page 1: MIS 451 Building Business Intelligence Systems Demo on Classification and Clustering.](https://reader036.fdocuments.in/reader036/viewer/2022062518/5697bf951a28abf838c90f5c/html5/thumbnails/1.jpg)
MIS 451
Building Business Intelligence Systems
Demo on Classification and Clustering
![Page 2: MIS 451 Building Business Intelligence Systems Demo on Classification and Clustering.](https://reader036.fdocuments.in/reader036/viewer/2022062518/5697bf951a28abf838c90f5c/html5/thumbnails/2.jpg)
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Iris
Irises are wonderful garden plants that can grow in Deserts Swamps Cold weather Temperate climates
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Iris – Vincent Van Gogh’s Iris Paintings
![Page 4: MIS 451 Building Business Intelligence Systems Demo on Classification and Clustering.](https://reader036.fdocuments.in/reader036/viewer/2022062518/5697bf951a28abf838c90f5c/html5/thumbnails/4.jpg)
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Iris --- Iris Setosa
Grow in Alaska, Japan, China and Northern Asia
![Page 5: MIS 451 Building Business Intelligence Systems Demo on Classification and Clustering.](https://reader036.fdocuments.in/reader036/viewer/2022062518/5697bf951a28abf838c90f5c/html5/thumbnails/5.jpg)
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Iris --- Iris Versicolor
Grow in the North of USA
![Page 6: MIS 451 Building Business Intelligence Systems Demo on Classification and Clustering.](https://reader036.fdocuments.in/reader036/viewer/2022062518/5697bf951a28abf838c90f5c/html5/thumbnails/6.jpg)
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Iris --- Iris Virginica
Grow in the Southeast of USA
![Page 7: MIS 451 Building Business Intelligence Systems Demo on Classification and Clustering.](https://reader036.fdocuments.in/reader036/viewer/2022062518/5697bf951a28abf838c90f5c/html5/thumbnails/7.jpg)
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Classification – Iris data
1 5.10 3.50 1.40 0.20 Iris-setosa
Sepal Length
Sepal Width
Petal Length
Petal Width Iris class
![Page 8: MIS 451 Building Business Intelligence Systems Demo on Classification and Clustering.](https://reader036.fdocuments.in/reader036/viewer/2022062518/5697bf951a28abf838c90f5c/html5/thumbnails/8.jpg)
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Clustering – Bank data
female 18.0 2 449 blue 5
Gender Age Number of siblings
Income EducationProduct Type
1-6 gender 10-15 age 24-25 number of siblings
30-36 income 37-43 education
45-45 product type (CD, Saving, Checking, etc.)