This section describes main characteristics of the page-blocks data set and its attributes: 
				
		General information
		
		
		
		| Page Blocks Classification data set | 
		 
		
		
		| Type | Classification | Origin | Real world | 
		 
		
		| Features  | 10 | (Real / Integer / Nominal) | (4 / 6 / 0) | 
		 
					
			| Instances | 5472 | 
			Classes | 5 | 			 
			
			| Missing values? | No | 		 
		
		 
		 
		
		Attribute description
		
		
						
				| Attribute | Domain | 
				 
				
			| Height | [1, 804] |  
| Lenght | [1, 553] |  
| Area | [7, 143993] |  
| Eccen | [0.0070, 537.0] |  
| P_black | [0.052, 1.0] |  
| P_and | [0.062, 1.0] |  
| Mean_tr | [1.0, 4955.0] |  
| Blackpix | [1, 33017] |  
| Blackand | [7, 46133] |  
| Wb_trans | [1, 3212] |  
| Class | {1, 2, 3, 4, 5} |  
 
			
			 
				 
		
				
		
		
		
		
		
		
		
		
		
		
		
		
		
		
		
		
					
			Additional information
			
			This database contain blocks of the page layout of a document that has been detected by a segmentation process.
 
 The task is to determine the type of block: Text (1), Horizontal line (2), Graphic (3), Vertical line (4) or Picture (5). 
			 
			
 
  
			
				
		
		
		
		
		In this section you can download some files related to the page-blocks data set: 
		
			
		
			- The complete data set already formatted in KEEL format can be downloaded from 
				here
 .			 
			- A copy of the data set already partitioned by means of a 10-folds cross validation procedure can be downloaded from here
 . 
			- A copy of the data set already partitioned by means of a 5-folds cross validation procedure can be downloaded from here
 . 
		
		- The header file associated to this data set can be downloaded from here
 . 
			
			- This is not a native data set from the KEEL project. It has been obtained from the UCI Machine Learning Repository. The original page where the data set can be found is: http://archive.ics.uci.edu/ml/datasets/Page+Blocks+Classification.
 		 
	
	
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