# Weather Dataset ## Dataset ``` % This is a comment about the data set. % This data describes examples of whether to play % a game or not depending on weather conditions. @relation letsPlay @attribute outlook {sunny, overcast, rainy} @attribute temperature real @attribute humidity real @attribute windy {TRUE, FALSE} @attribute play {yes, no} @data sunny,85,FALSE,no sunny,90,TRUE,no overcast,86,FALSE,yes rainy,96,FALSE,yes rainy,80,FALSE,yes rainy,70,TRUE,no overcast,65,TRUE,yes sunny,95,FALSE,no sunny,70,FALSE,yes rainy,80,FALSE,yes sunny,70,TRUE,yes overcast,90,TRUE,yes overcast,75,FALSE,yes rainy,91,TRUE,no ``` ## Output ``` === Run information === Scheme: weka.classifiers.bayes.NaiveBayes Relation: letsPlay Instances: 14 Attributes: 5 outlook temperature humidity windy play Test mode: evaluate on training data === Classifier model (full training set) === Naive Bayes Classifier Class Attribute yes no (0.63) (0.38) =============================== outlook sunny 3.0 4.0 overcast 5.0 1.0 rainy 4.0 3.0 [total] 12.0 8.0 temperature mean 72.9697 74.8364 std. dev. 5.2304 7.384 weight sum 9 5 precision 1.9091 1.9091 humidity mean 78.8395 86.1111 std. dev. 9.8023 9.2424 weight sum 9 5 precision 3.4444 3.4444 windy TRUE 4.0 4.0 FALSE 7.0 3.0 [total] 11.0 7.0 Time taken to build model: 0 seconds === Evaluation on training set === Time taken to test model on training data: 0.01 seconds === Summary === Correctly Classified Instances 13 92.8571 % Incorrectly Classified Instances 1 7.1429 % Kappa statistic 0.8372 Mean absolute error 0.2798 Root mean squared error 0.3315 Relative absolute error 60.2576 % Root relative squared error 69.1352 % Total Number of Instances 14 ``` # Medical Dataset ## Dataset ``` ```@relation medical @attribute Temperature {Low,Moderate,High} @attribute Skin {Pale,Normal,Red} @attribute BloodPressure {Normal,High} @attribute BlockedNose {True,False} @attribute Diagnosis {N,B} @data Low, Pale, Normal, True, N Moderate, Pale, Normal, True, B High, Normal, High, False, N Moderate, Pale, Normal, False, B High, Red, High, False, N High, Red, High, True, N Moderate, Red, High, False, B Low, Normal, High, False, B Low, Pale, Normal, False, B Low, Normal, Normal, False, B High, Normal, Normal, True, B Moderate, Normal, High, True, B Moderate, Red, Normal, False, B Low, Normal, High, True, N``` ``` ## Output ``` === Run information === Scheme: weka.classifiers.bayes.NaiveBayes Relation: diagnosis Instances: 14 Attributes: 5 Temperature Skin BloodPressure BlockedNose Diagnosis Test mode: evaluate on training data === Classifier model (full training set) === Naive Bayes Classifier Class Attribute N B (0.38) (0.63) ============================== Temperature Low 3.0 4.0 Moderate 1.0 6.0 High 4.0 2.0 [total] 8.0 12.0 Skin Pale 2.0 4.0 Normal 3.0 5.0 Red 3.0 3.0 [total] 8.0 12.0 BloodPressure Normal 2.0 7.0 High 5.0 4.0 [total] 7.0 11.0 BlockedNose True 4.0 4.0 False 3.0 7.0 [total] 7.0 11.0 Time taken to build model: 0 seconds === Evaluation on training set === Time taken to test model on training data: 0 seconds === Summary === Correctly Classified Instances 12 85.7143 % Incorrectly Classified Instances 2 14.2857 % Kappa statistic 0.6889 Mean absolute error 0.2635 Root mean squared error 0.3272 Relative absolute error 56.7565 % Root relative squared error 68.2385 % Total Number of Instances 14 ``` # Using Test Data ## Test Data ``` @relation medical @attribute Temperature {Low,Moderate,High} @attribute Skin {Pale,Normal,Red} @attribute BloodPressure {Normal,High} @attribute BlockedNose {True,False} @attribute Diagnosis {N,B} @data Low,Normal,High,True,N Low,?,Normal,True,B Moderate,Normal,High,True,B ``` ## Output ``` === Run information === Scheme: weka.classifiers.bayes.NaiveBayes Relation: medical Instances: 14 Attributes: 5 Temperature Skin BloodPressure BlockedNose Diagnosis Test mode: user supplied test set: size unknown (reading incrementally) === Classifier model (full training set) === Naive Bayes Classifier Class Attribute N B (0.38) (0.63) ============================== Temperature Low 3.0 4.0 Moderate 1.0 6.0 High 4.0 2.0 [total] 8.0 12.0 Skin Pale 2.0 4.0 Normal 3.0 5.0 Red 3.0 3.0 [total] 8.0 12.0 BloodPressure Normal 2.0 7.0 High 5.0 4.0 [total] 7.0 11.0 BlockedNose True 4.0 4.0 False 3.0 7.0 [total] 7.0 11.0 Time taken to build model: 0 seconds === Predictions on test set === inst# actual predicted error prediction 1 1:N 1:N 0.652 2 2:B 2:B 0.677 3 2:B 2:B 0.706 === Evaluation on test set === Time taken to test model on supplied test set: 0 seconds === Summary === Correctly Classified Instances 3 100 % Incorrectly Classified Instances 0 0 % Kappa statistic 1 Mean absolute error 0.3215 Root mean squared error 0.3223 Relative absolute error 70.1487 % Root relative squared error 68.0965 % Total Number of Instances 3 ```