Labor Relations
Donated on 10/31/1988
From Collective Bargaining Review
Dataset Characteristics
Multivariate
Subject Area
Social Science
Associated Tasks
-
Feature Type
Categorical, Integer, Real
# Instances
57
# Features
16
Dataset Information
Additional Information
Data was used to test 2 tier approach with learning from positive and negative examples
Has Missing Values?
No
Variable Information
1. dur: duration of agreement [1..7] 2 wage1.wage : wage increase in first year of contract [2.0 .. 7.0] 3 wage2.wage : wage increase in second year of contract [2.0 .. 7.0] 4 wage3.wage : wage increase in third year of contract [2.0 .. 7.0] 5 cola : cost of living allowance [none, tcf, tc] 6 hours.hrs : number of working hours during week [35 .. 40] 7 pension : employer contributions to pension plan [none, ret_allw, empl_contr] 8 stby_pay : standby pay [2 .. 25] 9 shift_diff : shift differencial : supplement for work on II and III shift [1 .. 25] 10 educ_allw.boolean : education allowance [true false] 11 holidays : number of statutory holidays [9 .. 15] 12 vacation : number of paid vacation days [ba, avg, gnr] 13 lngtrm_disabil.boolean : employer's help during employee longterm disability [true , false] 14 dntl_ins : employers contribution towards the dental plan [none, half, full] 15 bereavement.boolean : employer's financial contribution towards the covering the costs of bereavement [true , false] 16 empl_hplan : employer's contribution towards the health plan [none, half, full]
Dataset Files
| File | Size |
|---|---|
| labor-negotiations.test | 6.9 KB |
| labor-negotiations.data | 6.4 KB |
| C4.5/labor-neg.names | 3.9 KB |
| labor-negotiations.names | 3.1 KB |
| C4.5/labor-neg.data | 2.4 KB |
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pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset labor_relations = fetch_ucirepo(id=56) # data (as pandas dataframes) X = labor_relations.data.features y = labor_relations.data.targets # metadata print(labor_relations.metadata) # variable information print(labor_relations.variables)
Labor Relations [Dataset]. (1988). UCI Machine Learning Repository. https://doi.org/10.24432/C5CP4Q.
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.