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