The SAS System 18:28 Saturday, March 10, Plot of Canonical Variables Identified by Cluster
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1 The SAS System 18:28 Saturday, March 10, The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=2 Maxiter=10 Converge=0.02 Initial Seeds Cluster SepalLength SepalWidth PetalLength PetalWidth Minimum Distance Between Initial Seeds = Iteration History Relative Change in Cluster Seeds Iteration Criterion Convergence criterion is satisfied. Criterion Based on Final Seeds = Cluster Summary Cluster Frequency RMS Std Deviation MaximumDistance from Seed to Observation Radius Exceeded Nearest Cluster Distance Between Cluster Centroids Statistics for Variables Variable Total STD Within STD R-Square RSQ/(1-RSQ) SepalLength SepalWidth PetalLength PetalWidth OVER-ALL Pseudo F Statistic = Approximate Expected Over-All R-Squared =
2 The SAS System 18:28 Saturday, March 10, The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=2 Maxiter=10 Converge=0.02 Cubic Clustering Criterion = WARNING: The two values above are invalid for correlated variables. Cluster Means Cluster SepalLength SepalWidth PetalLength PetalWidth Cluster Standard Deviations Cluster SepalLength SepalWidth PetalLength PetalWidth
3 The SAS System 18:28 Saturday, March 10, The FREQ Procedure Frequency Percent Row Pct Col Pct Table of CLUSTER by Species Species(Iris Species) CLUSTER(Cluster) Setosa Versicolor Virginica Total Total
4 The SAS System 18:28 Saturday, March 10, The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=3 Maxiter=10 Converge=0.02 Initial Seeds Cluster SepalLength SepalWidth PetalLength PetalWidth Minimum Distance Between Initial Seeds = Iteration History Relative Change in Cluster Seeds Iteration Criterion Convergence criterion is satisfied. Criterion Based on Final Seeds = Cluster Summary Cluster Frequency RMS Std Deviation MaximumDistance from Seed to Observation Radius Exceeded Nearest Cluster Distance Between Cluster Centroids Statistics for Variables Variable Total STD Within STD R-Square RSQ/(1-RSQ) SepalLength SepalWidth PetalLength PetalWidth OVER-ALL Pseudo F Statistic =
5 The SAS System 18:28 Saturday, March 10, The FASTCLUS Procedure Replace=FULL Radius=0 Maxclusters=3 Maxiter=10 Converge=0.02 Approximate Expected Over-All R-Squared = Cubic Clustering Criterion = WARNING: The two values above are invalid for correlated variables. Cluster Means Cluster SepalLength SepalWidth PetalLength PetalWidth Cluster Standard Deviations Cluster SepalLength SepalWidth PetalLength PetalWidth
6 The SAS System 18:28 Saturday, March 10, The FREQ Procedure Frequency Percent Row Pct Col Pct Table of CLUSTER by Species Species(Iris Species) CLUSTER(Cluster) Setosa Versicolor Virginica Total Total
7 The SAS System 18:28 Saturday, March 10, Canonical Discriminant Analysis of Iris Clusters The CANDISC Procedure Total Sample Size 150 DF Total 149 Variables 4 DF Within Classes 147 Classes 3 DF Between Classes 2 Number of Observations Read 150 Number of Observations Used 150 Class Level Information CLUSTER Variable Name Frequency Weight Proportion 1 _ _ _
8 The SAS System 18:28 Saturday, March 10, Canonical Discriminant Analysis of Iris Clusters The CANDISC Procedure Univariate Test Statistics F Statistics, Num DF=2, Den DF=147 Variable Label Total Standard Deviation Pooled Standard Deviation Between Standard Deviation R-Square R-Square / (1-RSq) F Value Pr > F SepalLength Sepal Length (mm) <.0001 SepalWidth Sepal Width (mm) <.0001 PetalLength Petal Length (mm) <.0001 PetalWidth Petal Width (mm) <.0001 Average R-Square Unweighted Weighted by Variance Multivariate Statistics and F Approximations S=2 M=0.5 N=71 Statistic Value F Value Num DF Den DF Pr > F Wilks' Lambda <.0001 Pillai's Trace <.0001 Hotelling-Lawley Trace <.0001 Roy's Greatest Root <.0001 NOTE: F Statistic for Roy's Greatest Root is an upper bound. NOTE: F Statistic for Wilks' Lambda is exact.
9 The SAS System 18:28 Saturday, March 10, Canonical Discriminant Analysis of Iris Clusters The CANDISC Procedure Eigenvalues of Inv(E)*H = CanRsq/(1-CanRsq) Canonical Correlation Adjusted Canonical Correlation Approximate Standard Error Squared Canonical Correlation Eigenvalue Difference Proportion Cumulative Test of H0: The canonical correlations in the current row and all that follow are zero Likelihood Ratio Approximate F Value Num DF Den DF Pr > F < <.0001
10 The SAS System 18:28 Saturday, March 10, Canonical Discriminant Analysis of Iris Clusters The CANDISC Procedure Total Canonical Structure Variable Label Can1 Can2 SepalLength Sepal Length (mm) SepalWidth Sepal Width (mm) PetalLength Petal Length (mm) PetalWidth Petal Width (mm) Between Canonical Structure Variable Label Can1 Can2 SepalLength Sepal Length (mm) SepalWidth Sepal Width (mm) PetalLength Petal Length (mm) PetalWidth Petal Width (mm) Pooled Within Canonical Structure Variable Label Can1 Can2 SepalLength Sepal Length (mm) SepalWidth Sepal Width (mm) PetalLength Petal Length (mm) PetalWidth Petal Width (mm)
11 The SAS System 18:28 Saturday, March 10, Canonical Discriminant Analysis of Iris Clusters The CANDISC Procedure Total-Sample Standardized Canonical Coefficients Variable Label Can1 Can2 SepalLength Sepal Length (mm) SepalWidth Sepal Width (mm) PetalLength Petal Length (mm) PetalWidth Petal Width (mm) Pooled Within-Class Standardized Canonical Coefficients Variable Label Can1 Can2 SepalLength Sepal Length (mm) SepalWidth Sepal Width (mm) PetalLength Petal Length (mm) PetalWidth Petal Width (mm) Raw Canonical Coefficients Variable Label Can1 Can2 SepalLength Sepal Length (mm) SepalWidth Sepal Width (mm) PetalLength Petal Length (mm) PetalWidth Petal Width (mm) Class Means on Canonical Variables CLUSTER Can1 Can
12 18:28 Saturday, March 10, Can Can1 Cluster 2 3 1
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