Naive Bayes (simple)

Class >50K: P(C) = 0.24082548

Attribute age
'(-inf-0.054795]'	0.00076433
'(0.054795-0.082192]'	0.0033121 
'(0.082192-0.136986]'	0.02917197
'(0.136986-0.164384]'	0.03235669
'(0.164384-0.246575]'	0.1522293 
'(0.246575-0.356164]'	0.28101911
'(0.356164-0.506849]'	0.33503185
'(0.506849-0.60274]'	0.10802548
'(0.60274-inf)'	0.05808917



Attribute workclass
Private	0.64821102
Self-emp-not-inc	0.09467224
Self-emp-inc	0.08135283
Federal-gov	0.04857665
Local-gov	0.08069992
State-gov	0.04622617
Without-pay	0.00013058
Never-worked	0.00013058



Attribute fnlwgt
'All'	1         



Attribute education
Bachelors	0.28280514
Some-college	0.17665776
11th	0.00776378
HS-grad	0.21331297
Prof-school	0.05396462
Assoc-acdm	0.03385516
Assoc-voc	0.04607356
9th	0.0035637 
7th-8th	0.00521828
12th	0.00432735
Masters	0.12218404
1st-4th	0.00089093
10th	0.00801833
Doctorate	0.03907344
5th-6th	0.00216368
Preschool	0.00012728



Attribute education-num
'(-inf-0.466667]'	0.03121814
'(0.466667-0.533333]'	0.21355759
'(0.533333-0.6]'	0.17686035
'(0.6-0.733333]'	0.07989297
'(0.733333-0.8]'	0.28312946
'(0.8-0.866667]'	0.12232416
'(0.866667-inf)'	0.09301733



Attribute marital-status
Married-civ-spouse	0.85282875
Divorced	0.05912334
Never-married	0.06269113
Separated	0.00853721
Widowed	0.01095821
Married-spouse-absent	0.00445973
Married-AF-spouse	0.00140163



Attribute occupation
Tech-support	0.03705637
Craft-repair	0.12134656
Other-service	0.01800626
Sales	0.12839248
Exec-managerial	0.25691545
Prof-specialty	0.24269311
Handlers-cleaners	0.01135177
Machine-op-inspct	0.03275052
Adm-clerical	0.06628392
Farming-fishing	0.0151357 
Transport-moving	0.04188413
Priv-house-serv	0.00026096
Protective-serv	0.0276618 
Armed-Forces	0.00026096



Attribute relationship
Wife	0.09506818
Own-child	0.00866573
Husband	0.75430101
Not-in-family	0.10921371
Other-relative	0.00484262
Unmarried	0.02790875



Attribute race
White	0.90721387
Asian-Pac-Islander	0.03530461
Amer-Indian-Eskimo	0.00471578
Other	0.00331379
Black	0.04945195



Attribute sex
Female	0.15045263
Male	0.84954737



Attribute capital-gain
'(-inf-0]'	0.78475051
'(0-0.02993]'	0.00012729
'(0.02993-0.03103]'	0.0115835 
'(0.03103-0.04101]'	0.00012729
'(0.04101-0.04386]'	0.00751018
'(0.04386-0.0465]'	0.00012729
'(0.0465-0.04787]'	0.00343686
'(0.04787-0.04931]'	0.00012729
'(0.04931-0.04934]'	0.00101833
'(0.04934-0.050601]'	0.00012729
'(0.050601-0.051781]'	0.01247454
'(0.051781-0.054551]'	0.00012729
'(0.054551-0.065141]'	0.00267312
'(0.065141-0.068491]'	0.00012729
'(0.068491-inf)'	0.17566191



Attribute capital-loss
'(-inf-0.353306]'	0.9040224 
'(0.353306-0.359045]'	0.00330957
'(0.359045-0.416896]'	0.00038187
'(0.416896-0.424242]'	0.00712831
'(0.424242-0.43067]'	0.00012729
'(0.43067-0.436639]'	0.04442464
'(0.436639-0.453168]'	0.00012729
'(0.453168-0.453857]'	0.02151222
'(0.453857-0.496556]'	0.00012729
'(0.496556-0.499082]'	0.00101833
'(0.499082-0.506428]'	0.00025458
'(0.506428-0.545684]'	0.00445519
'(0.545684-0.561065]'	0.00903768
'(0.561065-0.8455]'	0.00394603
'(0.8455-inf)'	0.00012729



Attribute hours-per-week
'(-inf-0.336735]'	0.04944565
'(0.336735-0.387755]'	0.04485791
'(0.387755-0.408163]'	0.41480821
'(0.408163-0.489796]'	0.13635784
'(0.489796-0.653061]'	0.31795591
'(0.653061-inf)'	0.03657449



Attribute native-country
United-States	0.92709411
Cambodia	0.00103413
England	0.00400724
Puerto-Rico	0.00168046
Canada	0.00517063
Germany	0.00581696
Outlying-US(Guam-USVI-etc)	0.00012927
India	0.0052999 
Japan	0.00323164
Greece	0.00116339
South	0.00219752
China	0.00271458
Cuba	0.00336091
Iran	0.00245605
Honduras	0.00025853
Philippines	0.00801448
Italy	0.00336091
Poland	0.00168046
Jamaica	0.00142192
Vietnam	0.00077559
Mexico	0.00439504
Portugal	0.00064633
Ireland	0.00077559
France	0.00168046
Dominican-Republic	0.0003878 
Laos	0.0003878 
Ecuador	0.00064633
Taiwan	0.00271458
Haiti	0.00064633
Columbia	0.0003878 
Hungary	0.00051706
Guatemala	0.00051706
Nicaragua	0.0003878 
Scotland	0.00051706
Thailand	0.00051706
Yugoslavia	0.00090486
El-Salvador	0.00129266
Trinadad&Tobago	0.0003878 
Peru	0.0003878 
Hong	0.00090486
Holand-Netherlands	0.00012927





Class <=50K: P(C) = 0.75917452

Attribute age
'(-inf-0.054795]'	0.12641029
'(0.054795-0.082192]'	0.06542925
'(0.082192-0.136986]'	0.12260908
'(0.136986-0.164384]'	0.05774597
'(0.164384-0.246575]'	0.16260261
'(0.246575-0.356164]'	0.17578551
'(0.356164-0.506849]'	0.15969105
'(0.506849-0.60274]'	0.06591451
'(0.60274-inf)'	0.06381172



Attribute workclass
Private	0.76827102
Self-emp-not-inc	0.07875926
Self-emp-inc	0.02144435
Federal-gov	0.02555994
Local-gov	0.06398648
State-gov	0.04098254
Without-pay	0.00064983
Never-worked	0.00034658



Attribute fnlwgt
'All'	1         



Attribute education
Bachelors	0.12673836
Some-college	0.23872089
11th	0.04511643
HS-grad	0.35684832
Prof-school	0.00622574
Assoc-acdm	0.03246281
Assoc-voc	0.0413163 
9th	0.01972833
7th-8th	0.02453913
12th	0.01621119
Masters	0.03092658
1st-4th	0.00658959
10th	0.03525226
Doctorate	0.00436611
5th-6th	0.01285576
Preschool	0.0021022 



Attribute education-num
'(-inf-0.466667]'	0.16217091
'(0.466667-0.533333]'	0.3569782 
'(0.533333-0.6]'	0.23880778
'(0.6-0.733333]'	0.07376552
'(0.733333-0.8]'	0.12678449
'(0.8-0.866667]'	0.03093784
'(0.866667-inf)'	0.01055526



Attribute marital-status
Married-civ-spouse	0.33505884
Divorced	0.1609981 
Never-married	0.41222146
Separated	0.03882396
Widowed	0.03676143
Married-spouse-absent	0.01557002
Married-AF-spouse	0.00056618



Attribute occupation
Tech-support	0.02798718
Craft-repair	0.13737978
Other-service	0.13685989
Sales	0.1155879 
Exec-managerial	0.09093666
Prof-specialty	0.09886492
Handlers-cleaners	0.05567109
Machine-op-inspct	0.07594663
Adm-clerical	0.14140889
Farming-fishing	0.03812495
Transport-moving	0.05536782
Priv-house-serv	0.00645525
Protective-serv	0.01901915
Armed-Forces	0.00038991



Attribute relationship
Wife	0.03332524
Own-child	0.20229718
Husband	0.29426515
Not-in-family	0.30130227
Other-relative	0.03821888
Unmarried	0.13059128



Attribute race
White	0.8372093 
Asian-Pac-Islander	0.0308999 
Amer-Indian-Eskimo	0.01116279
Other	0.00998989
Black	0.11073812



Attribute sex
Female	0.38803495
Male	0.61196505



Attribute capital-gain
'(-inf-0]'	0.95759046
'(0-0.02993]'	0.0191227 
'(0.02993-0.03103]'	0.00032343
'(0.03103-0.04101]'	0.01253285
'(0.04101-0.04386]'	0.00052557
'(0.04386-0.0465]'	0.00266828
'(0.0465-0.04787]'	0.00004043
'(0.04787-0.04931]'	0.00076814
'(0.04931-0.04934]'	0.00004043
'(0.04934-0.050601]'	0.00287043
'(0.050601-0.051781]'	0.00004043
'(0.051781-0.054551]'	0.00048514
'(0.054551-0.065141]'	0.00072771
'(0.065141-0.068491]'	0.001415  
'(0.068491-inf)'	0.000849  



Attribute capital-loss
'(-inf-0.353306]'	0.97420659
'(0.353306-0.359045]'	0.00004043
'(0.359045-0.416896]'	0.0140287 
'(0.416896-0.424242]'	0.00008086
'(0.424242-0.43067]'	0.00161714
'(0.43067-0.436639]'	0.000566  
'(0.436639-0.453168]'	0.00080857
'(0.453168-0.453857]'	0.00004043
'(0.453857-0.496556]'	0.004528  
'(0.496556-0.499082]'	0.00004043
'(0.499082-0.506428]'	0.00125328
'(0.506428-0.545684]'	0.00185971
'(0.545684-0.561065]'	0.00004043
'(0.561065-0.8455]'	0.000566  
'(0.8455-inf)'	0.00032343



Attribute hours-per-week
'(-inf-0.336735]'	0.21018361
'(0.336735-0.387755]'	0.07401116
'(0.387755-0.408163]'	0.4853191 
'(0.408163-0.489796]'	0.08149317
'(0.489796-0.653061]'	0.12727493
'(0.653061-inf)'	0.02171803



Attribute native-country
United-States	0.9044565 
Cambodia	0.00053445
England	0.00250781
Puerto-Rico	0.0042345 
Canada	0.00341227
Germany	0.0038645 
Outlying-US(Guam-USVI-etc)	0.00061667
India	0.00250781
Japan	0.00160335
Greece	0.00090446
South	0.00267226
China	0.00230225
Cuba	0.00291893
Iran	0.0010689 
Honduras	0.00053445
Philippines	0.00567341
Italy	0.00201447
Poland	0.00201447
Jamaica	0.00296004
Vietnam	0.00259003
Mexico	0.02511922
Portugal	0.0013978 
Ireland	0.00082223
France	0.00074001
Dominican-Republic	0.0028367 
Laos	0.0006989 
Ecuador	0.00102779
Taiwan	0.00131557
Haiti	0.00168558
Columbia	0.00238448
Hungary	0.00045223
Guatemala	0.00254892
Nicaragua	0.00135668
Scotland	0.00041112
Thailand	0.00065779
Yugoslavia	0.00045223
El-Salvador	0.00402894
Trinadad&Tobago	0.00074001
Peru	0.00123335
Hong	0.00061667
Holand-Netherlands	0.00008222






=== Error on training data ===

Correctly Classified Instances       27346               83.9839 %
Incorrectly Classified Instances      5215               16.0161 %
Mean absolute error                      0.1751
Root mean squared error                  0.3406
Relative absolute error                 47.8946 %
Root relative squared error             79.6496 %
Total Number of Instances            32561     


=== Confusion Matrix ===

     a     b   <-- classified as
  6222  1619 |     a = >50K
  3596 21124 |     b = <=50K


=== Error on test data ===

Correctly Classified Instances       13720               84.27   %
Incorrectly Classified Instances      2561               15.73   %
Mean absolute error                      0.1745
Root mean squared error                  0.3402
Relative absolute error                 48.0408 %
Root relative squared error             80.0963 %
Total Number of Instances            16281     


=== Confusion Matrix ===

     a     b   <-- classified as
  3051   795 |     a = >50K
  1766 10669 |     b = <=50K