6.4 KiB
Executable File
6.4 KiB
Executable File
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