This study was made by the BMW dataset from Kaggle website here bellow the results gotten using the Weka software: === Run information ===

Scheme: weka.classifiers.bayes.NaiveBayes Relation: bmwreponses Instances: 3000 Attributes: 4 IncomeBracket FirstPurchase LastPurchase responded Test mode: 10-fold cross-validation

=== Classifier model (full training set) ===

Naive Bayes Classifier

Class Attribute 1 0 (0.51) (0.49) ======================================== IncomeBracket 0 361.0 322.0 1 115.0 147.0 2 190.0 202.0 3 142.0 108.0 4 186.0 196.0 5 262.0 249.0 6 127.0 140.0 7 150.0 119.0 [total] 1533.0 1483.0

FirstPurchase mean 200077.2645 200130.909 std. dev. 318.6108 309.5966 weight sum 1525 1475 precision 10.9407 10.9407

LastPurchase mean 200556.7842 200547.8182 std. dev. 52.0186 47.6155 weight sum 1525 1475 precision 8.6522 8.6522

Time taken to build model: 0.01 seconds

=== Stratified cross-validation === === Summary ===

Correctly Classified Instances 1643 54.7667 % Incorrectly Classified Instances 1357 45.2333 % Kappa statistic 0.0952 Mean absolute error 0.4896 Root mean squared error 0.4963 Relative absolute error 97.9491 % Root relative squared error 99.2769 % Total Number of Instances 3000

=== Detailed Accuracy By Class ===

TP Rate FP Rate Precision Recall F-Measure MCC ROC Area PRC Area Class 0.550 0.455 0.556 0.550 0.553 0.095 0.572 0.573 1 0.545 0.450 0.540 0.545 0.542 0.095 0.572 0.548 0 Weighted Avg. 0.548 0.452 0.548 0.548 0.548 0.095 0.572 0.561

=== Confusion Matrix ===

a b <-- classified as 839 686 | a = 1 671 804 | b = 0

interpret and conclude about this data , thank you