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Model name: am_laurier
Number of iterations = 3
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Iteration 1
Accuracy: 66.00%
Accuracy (normalised for class sizes): 66.00%
Raw Confusion Matrix:
Truth		    A  	    B  	    C  	    D  	    E  	
Classification
    A  		     18	      3	      1	      7	      5	
    B  		      3	     26	      0	     14	      0	
    C  		      1	      4	     38	      1	      0	
    D  		      7	      7	      1	     18	      3	
    E  		     11	      0	      0	      0	     32	

Confusion Matrix percentage:
Truth		    A  	    B  	    C  	    D  	    E  	
Classification
    A  		 45.00%	  7.50%	  2.50%	 17.50%	 12.50%	
    B  		  7.50%	 65.00%	  0.00%	 35.00%	  0.00%	
    C  		  2.50%	 10.00%	 95.00%	  2.50%	  0.00%	
    D  		 17.50%	 17.50%	  2.50%	 45.00%	  7.50%	
    E  		 27.50%	  0.00%	  0.00%	  0.00%	 80.00%	
Matrix Key:
       A  : 1
       B  : 2
       C  : 3
       D  : 4
       E  : 5
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Iteration 2
Accuracy: 59.00%
Accuracy (normalised for class sizes): 59.00%
Raw Confusion Matrix:
Truth		    A  	    B  	    C  	    D  	    E  	
Classification
    A  		     20	      7	      1	      1	     10	
    B  		      5	     17	      2	     16	      1	
    C  		      1	      7	     36	      1	      3	
    D  		      3	      9	      1	     21	      2	
    E  		     11	      0	      0	      1	     24	

Confusion Matrix percentage:
Truth		    A  	    B  	    C  	    D  	    E  	
Classification
    A  		 50.00%	 17.50%	  2.50%	  2.50%	 25.00%	
    B  		 12.50%	 42.50%	  5.00%	 40.00%	  2.50%	
    C  		  2.50%	 17.50%	 90.00%	  2.50%	  7.50%	
    D  		  7.50%	 22.50%	  2.50%	 52.50%	  5.00%	
    E  		 27.50%	  0.00%	  0.00%	  2.50%	 60.00%	
Matrix Key:
       A  : 1
       B  : 2
       C  : 3
       D  : 4
       E  : 5
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Iteration 3
Accuracy: 56.50%
Accuracy (normalised for class sizes): 56.50%
Raw Confusion Matrix:
Truth		    A  	    B  	    C  	    D  	    E  	
Classification
    A  		     17	      3	      0	      4	      7	
    B  		      6	     17	     12	      8	      1	
    C  		      4	      3	     25	      3	      0	
    D  		     11	     17	      3	     25	      3	
    E  		      2	      0	      0	      0	     29	

Confusion Matrix percentage:
Truth		    A  	    B  	    C  	    D  	    E  	
Classification
    A  		 42.50%	  7.50%	  0.00%	 10.00%	 17.50%	
    B  		 15.00%	 42.50%	 30.00%	 20.00%	  2.50%	
    C  		 10.00%	  7.50%	 62.50%	  7.50%	  0.00%	
    D  		 27.50%	 42.50%	  7.50%	 62.50%	  7.50%	
    E  		  5.00%	  0.00%	  0.00%	  0.00%	 72.50%	
Matrix Key:
       A  : 1
       B  : 2
       C  : 3
       D  : 4
       E  : 5
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Overall Evaluation for am_laurier
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Overall Accuracy am_laurier: 60.50% Standard Deviation: 2.32
Overall Accuracy (normalised for class sizes) am_laurier: 60.50% Standard Deviation: 2.32
Raw Confusion Matrix:
Truth		    A  	    B  	    C  	    D  	    E  	
Classification
    A  		     55	     13	      2	     12	     22	
    B  		     14	     60	     14	     38	      2	
    C  		      6	     14	     99	      5	      3	
    D  		     21	     33	      5	     64	      8	
    E  		     24	      0	      0	      1	     85	

Confusion Matrix percentage:
Truth		    A  	    B  	    C  	    D  	    E  	
Classification
    A  		 45.83%	 10.83%	  1.67%	 10.00%	 18.33%	
    B  		 11.67%	 50.00%	 11.67%	 31.67%	  1.67%	
    C  		  5.00%	 11.67%	 82.50%	  4.17%	  2.50%	
    D  		 17.50%	 27.50%	  4.17%	 53.33%	  6.67%	
    E  		 20.00%	  0.00%	  0.00%	  0.83%	 70.83%	
Matrix Key:
       A  : 1
       B  : 2
       C  : 3
       D  : 4
       E  : 5
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