Upload
avon
View
26
Download
0
Tags:
Embed Size (px)
DESCRIPTION
Thank you for coming here!. Purpose of Experiment. Compare two visualization systems. You will play with one of them. . What will you do?. Learn a multidimensional visualization system; Use it to find features of a data set and record your result; A quick after-experiment feedback. - PowerPoint PPT Presentation
Citation preview
Thank you for coming here!
Purpose of Experiment Compare two visualization
systems. You will play with one of them.
What will you do? Learn a multidimensional
visualization system; Use it to find features of a data set
and record your result; A quick after-experiment feedback.
Schedule First, I will present ...Multidimensional dataHierarchical Parallel CoordinatesBrushingFeature findingIntroduce the visualization system
Schedule Then, You will do ...Experiment: -Find features of a given data set using the visualization system
-Record the features you find
Fill feedback form.
Outline Multidimensional Data How to represent multidimensional
data Parallel Coordinates Hierarchical Clustering Hierarchical Parallel Coordinates
Brushing Operation Feature Finding
Multidimensional DataExample: Iris Data
Scientists measured the sepal length, sepal width, petal length, petal width of many kinds of iris...
Multidimensional DataExample: Iris Data
sepallength
sepalwidth
petallength
petalwidth
5.1 3.5 1.4 0.24.9 3 1.4 0.2... ... ... ...5.9 3 5.1 1.8
Outline Multidimensional Data How to represent multidimensional
data Parallel Coordinates Hierarchical Clustering Hierarchical Parallel Coordinates
Brushing Operation Feature Finding
Parallel Coordinates One-Dimensional Data
1 2(1.6)
Parallel Coordinates 4-Dimensional Iris Data Set
sepallength
sepalwidth
petallength
petalwidth
5.1 3.5 1.4 0.24.9 3 1.4 0.2... ... ... ...5.9 3 5.1 1.8
5.1
3.5
sepallength
sepalwidth
petallength
petalwidth
5.1 3.5 1.4 0.2
1.4 0.2
Outline Multidimensional Data How to represent multidimensional
data Parallel Coordinates Hierarchical Clustering Hierarchical Parallel Coordinates
Brushing Operation Feature Finding
Hierarchical ClusteringHierarchical Cluster Tree
A cluster tree
Hierarchical ClusteringMean, Extent
P2
P1
C1
P1( 3, 6) p2( 5, 5)
Mean Point of C1 = (P1+P2)/2 = (4, 5.5)
Extent of C1:x:[3, 5] y:[5, 6]
x
y
Outline Multidimensional Data How to represent multidimensional
data Parallel Coordinates Hierarchical Clustering Hierarchical Parallel Coordinates
Brushing Operation Feature Finding
Outline Multidimensional Data How to represent multidimensional
data Parallel Coordinates Hierarchical Clustering Hierarchical Parallel Coordinates
Brushing Operation Feature Finding
BrushingBrushing - Highlighting part of the clusters to distinguish them from the other clusters.
Outline Multidimensional Data How to represent multidimensional
data Parallel Coordinates Hierarchical Clustering Hierarchical Parallel Coordinates
Brushing Operation Feature Finding
Feature FindingFeature - Anything you find from the data set. Cluster - A group of data items that are similar in all dimensions.Outlier - A data item that is similar to FEW or No other data items.
Other featuresYou can record anything else you find with the help of the visualization system.