MaximumLikelihood classifier newClassifier

Cross Validation
Number of classes = 2
   class 0.0: BaturaTrain_OthersMSI    
    accuracy = 0.9840 precision = 0.9690 correlation = 0.9685 errorRate = 0.0160
    TruePositives = 250.0000 FalsePositives = 8.0000 TrueNegatives = 242.0000 FalseNegatives = 0.0000
   class 1.0: BaturaTrain_SnowIceMSI   
    accuracy = 0.9840 precision = 1.0000 correlation = 0.9685 errorRate = 0.0160
    TruePositives = 242.0000 FalsePositives = 0.0000 TrueNegatives = 250.0000 FalseNegatives = 8.0000

Using Testing dataset, % correct predictions = 98.4000
Total samples = 1000
RMSE = 0.12649110640673517
Bias = -0.016000000000000014

Distribution:
   class 0.0: BaturaTrain_OthersMSI      500	 (50.0000%)
   class 1.0: BaturaTrain_SnowIceMSI     500	 (50.0000%)

Testing feature importance score:
Each feature is perturbed 3 times and the % correct predictions are averaged
The importance score is the original % correct prediction - average
   rank 1   feature 7  : Red_SWIR                 score: tp=0.8160 accuracy=0.4770 precision=0.2399 correlation=0.6666 errorRate=-0.4770 cost=-0.5068 GainRatio = 0.1532
   rank 2   feature 8  : NIR_SWIR                 score: tp=0.8100 accuracy=0.4843 precision=0.2572 correlation=0.6488 errorRate=-0.4843 cost=-0.5848 GainRatio = 0.1480
   rank 3   feature 1  : band_1                   score: tp=0.7040 accuracy=0.4493 precision=0.2273 correlation=0.5981 errorRate=-0.4493 cost=-0.4562 GainRatio = 0.1528
   rank 4   feature 2  : band_2                   score: tp=0.6973 accuracy=0.3690 precision=0.1122 correlation=0.5602 errorRate=-0.3690 cost=-0.1586 GainRatio = 0.1313
   rank 5   feature 3  : band_3                   score: tp=0.6920 accuracy=0.4547 precision=0.2206 correlation=0.6280 errorRate=-0.4547 cost=-0.4328 GainRatio = 0.1290
   rank 6   feature 5  : band_5                   score: tp=0.6340 accuracy=0.4233 precision=0.1882 correlation=0.6437 errorRate=-0.4233 cost=-0.3279 GainRatio = 0.1928
   rank 7   feature 4  : band_4                   score: tp=0.6047 accuracy=0.4480 precision=0.2171 correlation=0.6481 errorRate=-0.4480 cost=-0.4190 GainRatio = 0.0767
   rank 8   feature 6  : band_6                   score: tp=0.5893 accuracy=0.4217 precision=0.1914 correlation=0.6627 errorRate=-0.4217 cost=-0.3376 GainRatio = 0.2017
   rank 9   feature 10 : elevation                score: tp=0.4407 accuracy=0.4407 precision=0.2448 correlation=0.7476 errorRate=-0.4407 cost=-0.4655 GainRatio = 0.4764
   rank 10  feature 9  : ndsi                     score: tp=0.4287 accuracy=0.4287 precision=0.2198 correlation=0.7273 errorRate=-0.4287 cost=-0.4287 GainRatio = 0.1702