
==================================================================
DATASET iris information
      4 dimensions, 150 vectors, 50 positive, 100 negative

Result training 90%:
           Neighbors= 4
           Training time=0.0
           Accuracy=1.00

Final result: TEST 10%:
           Accuracy=1.00

==================================================================
DATASET wine information
      13 dimensions, 178 vectors, 59 positive, 119 negative

Result training 90%:
           Neighbors= 5
           Training time=0.0160000324249
           Accuracy=1.00

Final result: TEST 10%:
           Accuracy=0.94

==================================================================
DATASET dna information
      180 dimensions, 2000 vectors, 464 positive, 1536 negative

Result training 90%:
           Neighbors= 8
           Training time=0.0160000324249
           Accuracy=0.85

Final result: TEST 10%:
           Accuracy=0.84

==================================================================
DATASET vehicle information
      18 dimensions, 846 vectors, 212 positive, 634 negative

Result training 90%:
           Neighbors= 6
           Training time=0.0
           Accuracy=0.75

Final result: TEST 10%:
           Accuracy=0.69

==================================================================
DATASET segment information
      19 dimensions, 2310 vectors, 330 positive, 1980 negative

Result training 90%:
           Neighbors= 4
           Training time=0.0
           Accuracy=0.97

Final result: TEST 10%:
           Accuracy=0.96
