outlier_test.m

我上载的最后一个空间数据挖掘的例外点检测程序（共4个）,用matlab编的。

% 			README of Spatial Outlier Detection
% 				S. Shekhar & P. Zhang
% 				University of Minnesota
% 				
% Objective:
% 	Better understand concepts and methods for spatial outlier detection
% 	comparing to traditional ones.
% Requirement:
% 	Matlab
% 		
% Data:
% data.txt is an example dataset for spatial outlier detection illustration.
% It's a 30 x 2 matrix: first column is the spatial coordinates, and second
% column is the attribute value at the location. Each row is an instance.
% 
% Procedure:
% Open matlab, then type the script name for the spatial outlier detection
% demo.
% 
% The running script for spatial outlier detection is named Outlier_Demo.m
% In this script, the data were loaded into workspace. Then users have
% several sub-scripts to play with. It will calculate different outliers,
% and generate the figures used in the spatial outlier subsection in 
% the spatial data mining book chapter[SDM03].
% 
% (1)Show raw data 
% run Show_Data.m (remove % before Show_Data in the Outlier_Demo script)
% or type Show_Data in command line
% Output: Generate the Figure 3.4(a) in [SDM03]
% 
% (2)Show histogram for the attribute in data
% run Show_Hist.m (remove % before Show_Hist in the Outlier_Demo script)
% or type Show_Hist in command line
% Output: Generate the Figure 3.4 (b) in [SDM03]
% 
% (2)Global outlier detection
% run Outlier_Global.m (remove % before Outlier_Global in the Outlier_Demo script)
% or type Outlier_Global in command line
% Output: Generate a figure to show that G, the max value in the data, is the global outlier
% 
% (3)Outlier detection using Scatter Plot 
% run Outlier_Scatter.m (remove % before Outlier_Scatter in the Outlier_Demo script)
% or type Outlier_Scatter in command line
% Output: Generate the Figure 3.6(a) in [SDM03]
% 
% (4)Outlier detection using Variogram
% run Outlier_Variogram.m (remove % before Outlier_Variogram in the Outlier_Demo script)
% or type Outlier_Variogram in command line
% Output: Generate the Figure 3.5(a) in [SDM03]
% 
% (5)Outlier detection using Spatial test [GeoInfo03]
% run Outlier_Test.m (remove % before Outlier_Test in the Outlier_Demo script)
% or type Outlier_Test in command line
% Output: Generate the Figure 3.6(b) in [SDM03]
% 
% References:
% 
% [SDM03] Shashi Shekhar, Pusheng Zhang, Yan Huang, and Ranga Raju Vatsavai, "Spatial Data 
% Mining", as a book chapter to appear in "Data Mining: Next Generation Challenges and 
% Future Directions", Hillol Kargupta and Anupam Joshi(editors), AAAI/MIT Press, 2003
% 
% [GeoInfo03] Shashi Shekhar, Chang-Tien Lu, and Pusheng Zhang, A Unified Approach 
% to Detecting Spatial Outliers, GeoInformatica, An International Journal on 
% Advances of Computer Science for Geographic Information Systems, Volume 7, 
% Issue 2, 139-166, Kluwer Academic Publishers, June 2003, 

our = data;
for k=1:m
   our(k,2)=data(k,2)-nei(k,2);
end;

figure;
hold on;
plot(our(:,1),our(:,2),'ro','LineWidth',2,...
                'MarkerEdgeColor','k',...
                'MarkerFaceColor','g',...
                'MarkerSize',6);
plot(our(1,1),our(1,2),'ro','LineWidth',2,...
                'MarkerEdgeColor','k',...
                'MarkerFaceColor','r',...
                'MarkerSize',6);
plot(our(m,1),our(m,2),'ro','LineWidth',2,...
                'MarkerEdgeColor','k',...
                'MarkerFaceColor','r',...
                'MarkerSize',6);

title('Outliers Detected Using Spatial Test','fontsize',22);
xlabel('Location','fontsize',20);
ylabel('Statistical Test S(x)','fontsize',20);
text(4.8,3.4,'S \rightarrow','FontSize',14);
hold off;
%print -djpeg90 our3.jpg