slice_output.txt

Model Performance on Data Slices
===============================


Feature: workclass
-------------------
workclass: ?, Count: 389
Precision: 0.6538 | Recall: 0.4048 | F1: 0.5000

workclass: Federal-gov, Count: 191
Precision: 0.7971 | Recall: 0.7857 | F1: 0.7914

workclass: Local-gov, Count: 387
Precision: 0.7576 | Recall: 0.6818 | F1: 0.7177

workclass: Private, Count: 4,578
Precision: 0.7376 | Recall: 0.6404 | F1: 0.6856

workclass: Self-emp-inc, Count: 212
Precision: 0.7807 | Recall: 0.7542 | F1: 0.7672

workclass: Self-emp-not-inc, Count: 498
Precision: 0.7064 | Recall: 0.4904 | F1: 0.5789

workclass: State-gov, Count: 254
Precision: 0.7424 | Recall: 0.6712 | F1: 0.7050

workclass: Without-pay, Count: 4 (too few samples)
Precision: N/A | Recall: N/A | F1: N/A


Feature: education
-------------------
education: 10th, Count: 183
Precision: 0.4000 | Recall: 0.1667 | F1: 0.2353

education: 11th, Count: 225
Precision: 1.0000 | Recall: 0.2727 | F1: 0.4286

education: 12th, Count: 98
Precision: 1.0000 | Recall: 0.4000 | F1: 0.5714

education: 1st-4th, Count: 23
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

education: 5th-6th, Count: 62
Precision: 1.0000 | Recall: 0.5000 | F1: 0.6667

education: 7th-8th, Count: 141
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

education: 9th, Count: 115
Precision: 1.0000 | Recall: 0.3333 | F1: 0.5000

education: Assoc-acdm, Count: 198
Precision: 0.7000 | Recall: 0.5957 | F1: 0.6437

education: Assoc-voc, Count: 273
Precision: 0.6471 | Recall: 0.5238 | F1: 0.5789

education: Bachelors, Count: 1,053
Precision: 0.7523 | Recall: 0.7289 | F1: 0.7404

education: Doctorate, Count: 77
Precision: 0.8644 | Recall: 0.8947 | F1: 0.8793

education: HS-grad, Count: 2,085
Precision: 0.6594 | Recall: 0.4377 | F1: 0.5261

education: Masters, Count: 369
Precision: 0.8271 | Recall: 0.8551 | F1: 0.8409

education: Preschool, Count: 10
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

education: Prof-school, Count: 116
Precision: 0.8182 | Recall: 0.9643 | F1: 0.8852

education: Some-college, Count: 1,485
Precision: 0.6857 | Recall: 0.5199 | F1: 0.5914


Feature: marital-status
------------------------
marital-status: Divorced, Count: 920
Precision: 0.7600 | Recall: 0.3689 | F1: 0.4967

marital-status: Married-AF-spouse, Count: 4 (too few samples)
Precision: N/A | Recall: N/A | F1: N/A

marital-status: Married-civ-spouse, Count: 2,950
Precision: 0.7346 | Recall: 0.6900 | F1: 0.7116

marital-status: Married-spouse-absent, Count: 96
Precision: 1.0000 | Recall: 0.2500 | F1: 0.4000

marital-status: Never-married, Count: 2,126
Precision: 0.8302 | Recall: 0.4272 | F1: 0.5641

marital-status: Separated, Count: 209
Precision: 1.0000 | Recall: 0.4211 | F1: 0.5926

marital-status: Widowed, Count: 208
Precision: 1.0000 | Recall: 0.1579 | F1: 0.2727


Feature: occupation
--------------------
occupation: ?, Count: 389
Precision: 0.6538 | Recall: 0.4048 | F1: 0.5000

occupation: Adm-clerical, Count: 726
Precision: 0.6338 | Recall: 0.4688 | F1: 0.5389

occupation: Armed-Forces, Count: 3 (too few samples)
Precision: N/A | Recall: N/A | F1: N/A

occupation: Craft-repair, Count: 821
Precision: 0.6567 | Recall: 0.4862 | F1: 0.5587

occupation: Exec-managerial, Count: 838
Precision: 0.7952 | Recall: 0.7531 | F1: 0.7736

occupation: Farming-fishing, Count: 193
Precision: 0.5455 | Recall: 0.2143 | F1: 0.3077

occupation: Handlers-cleaners, Count: 273
Precision: 0.5714 | Recall: 0.3333 | F1: 0.4211

occupation: Machine-op-inspct, Count: 378
Precision: 0.5938 | Recall: 0.4043 | F1: 0.4810

occupation: Other-service, Count: 667
Precision: 1.0000 | Recall: 0.1923 | F1: 0.3226

occupation: Priv-house-serv, Count: 26
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

occupation: Prof-specialty, Count: 828
Precision: 0.7880 | Recall: 0.7679 | F1: 0.7778

occupation: Protective-serv, Count: 136
Precision: 0.7353 | Recall: 0.5952 | F1: 0.6579

occupation: Sales, Count: 729
Precision: 0.7273 | Recall: 0.6667 | F1: 0.6957

occupation: Tech-support, Count: 189
Precision: 0.7143 | Recall: 0.6863 | F1: 0.7000

occupation: Transport-moving, Count: 317
Precision: 0.6250 | Recall: 0.4688 | F1: 0.5357


Feature: relationship
----------------------
relationship: Husband, Count: 2,590
Precision: 0.7370 | Recall: 0.6923 | F1: 0.7140

relationship: Not-in-family, Count: 1,702
Precision: 0.7959 | Recall: 0.4149 | F1: 0.5455

relationship: Other-relative, Count: 178
Precision: 1.0000 | Recall: 0.3750 | F1: 0.5455

relationship: Own-child, Count: 1,019
Precision: 1.0000 | Recall: 0.1765 | F1: 0.3000

relationship: Unmarried, Count: 702
Precision: 0.9231 | Recall: 0.2667 | F1: 0.4138

relationship: Wife, Count: 322
Precision: 0.7132 | Recall: 0.6783 | F1: 0.6953


Feature: race
--------------
race: Amer-Indian-Eskimo, Count: 71
Precision: 0.6250 | Recall: 0.5000 | F1: 0.5556

race: Asian-Pac-Islander, Count: 193
Precision: 0.7857 | Recall: 0.7097 | F1: 0.7458

race: Black, Count: 599
Precision: 0.7273 | Recall: 0.6154 | F1: 0.6667

race: Other, Count: 55
Precision: 1.0000 | Recall: 0.6667 | F1: 0.8000

race: White, Count: 5,595
Precision: 0.7404 | Recall: 0.6373 | F1: 0.6850


Feature: sex
-------------
sex: Female, Count: 2,126
Precision: 0.7229 | Recall: 0.5150 | F1: 0.6015

sex: Male, Count: 4,387
Precision: 0.7445 | Recall: 0.6599 | F1: 0.6997


Feature: native-country
------------------------
native-country: ?, Count: 125
Precision: 0.7500 | Recall: 0.6774 | F1: 0.7119

native-country: Cambodia, Count: 3 (too few samples)
Precision: N/A | Recall: N/A | F1: N/A

native-country: Canada, Count: 22
Precision: 0.6667 | Recall: 0.7500 | F1: 0.7059

native-country: China, Count: 18
Precision: 1.0000 | Recall: 1.0000 | F1: 1.0000

native-country: Columbia, Count: 6
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Cuba, Count: 19
Precision: 0.6667 | Recall: 0.8000 | F1: 0.7273

native-country: Dominican-Republic, Count: 8
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Ecuador, Count: 5
Precision: 1.0000 | Recall: 0.5000 | F1: 0.6667

native-country: El-Salvador, Count: 20
Precision: 1.0000 | Recall: 1.0000 | F1: 1.0000

native-country: England, Count: 14
Precision: 0.6667 | Recall: 0.5000 | F1: 0.5714

native-country: France, Count: 5
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Germany, Count: 32
Precision: 0.8462 | Recall: 0.8462 | F1: 0.8462

native-country: Greece, Count: 7
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Guatemala, Count: 13
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Haiti, Count: 6
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Honduras, Count: 4 (too few samples)
Precision: N/A | Recall: N/A | F1: N/A

native-country: Hong, Count: 8
Precision: 0.5000 | Recall: 1.0000 | F1: 0.6667

native-country: Hungary, Count: 3 (too few samples)
Precision: N/A | Recall: N/A | F1: N/A

native-country: India, Count: 21
Precision: 0.8750 | Recall: 0.8750 | F1: 0.8750

native-country: Iran, Count: 12
Precision: 0.3333 | Recall: 0.2000 | F1: 0.2500

native-country: Ireland, Count: 5
Precision: 1.0000 | Recall: 1.0000 | F1: 1.0000

native-country: Italy, Count: 14
Precision: 0.7500 | Recall: 0.7500 | F1: 0.7500

native-country: Jamaica, Count: 13
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Japan, Count: 11
Precision: 0.7500 | Recall: 0.7500 | F1: 0.7500

native-country: Laos, Count: 4 (too few samples)
Precision: N/A | Recall: N/A | F1: N/A

native-country: Mexico, Count: 114
Precision: 1.0000 | Recall: 0.3333 | F1: 0.5000

native-country: Nicaragua, Count: 7
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Peru, Count: 5
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Philippines, Count: 35
Precision: 1.0000 | Recall: 0.6875 | F1: 0.8148

native-country: Poland, Count: 14
Precision: 0.6667 | Recall: 1.0000 | F1: 0.8000

native-country: Portugal, Count: 6
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Puerto-Rico, Count: 22
Precision: 0.8333 | Recall: 0.8333 | F1: 0.8333

native-country: Scotland, Count: 3 (too few samples)
Precision: N/A | Recall: N/A | F1: N/A

native-country: South, Count: 13
Precision: 0.3333 | Recall: 0.5000 | F1: 0.4000

native-country: Taiwan, Count: 11
Precision: 0.7500 | Recall: 0.7500 | F1: 0.7500

native-country: Thailand, Count: 5
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Trinadad&Tobago, Count: 3 (too few samples)
Precision: N/A | Recall: N/A | F1: N/A

native-country: United-States, Count: 5,870
Precision: 0.7392 | Recall: 0.6321 | F1: 0.6814

native-country: Vietnam, Count: 5
Precision: 0.0000 | Recall: 0.0000 | F1: 0.0000

native-country: Yugoslavia, Count: 2 (too few samples)
Precision: N/A | Recall: N/A | F1: N/A