OpenML
ibm-employee-performance

ibm-employee-performance

active ARFF Open Database License (ODbL) + Database Content License(DbCL) Visibility: public Uploaded 30-05-2022 by Florian Pfisterer
0 likes downloaded by 0 people , 0 total downloads 0 issues 0 downvotes
  • Computer Systems Machine Learning
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
IBM Employee Attrition Data The dataset used in the code pattern is supplied by Kaggle and contains HR analytics data of employees that stay and leave. The types of data include metrics such as education level, job satisfactions, and commmute distance. The dataset was obtained from https://github.com/IBM/employee-attrition-aif360. The dataset is available under the Open Dataset License and the Database Content License.

34 features

PerformanceRating (target)nominal2 unique values
0 missing
Agenumeric43 unique values
0 missing
BusinessTravelstring3 unique values
0 missing
DailyRatenumeric886 unique values
0 missing
Departmentstring3 unique values
0 missing
DistanceFromHomenumeric29 unique values
0 missing
Educationnumeric5 unique values
0 missing
EducationFieldstring6 unique values
0 missing
EmployeeCountnumeric1 unique values
0 missing
EmployeeNumbernumeric1470 unique values
0 missing
EnvironmentSatisfactionnumeric4 unique values
0 missing
Genderstring2 unique values
0 missing
HourlyRatenumeric71 unique values
0 missing
JobInvolvementnumeric4 unique values
0 missing
JobLevelnumeric5 unique values
0 missing
JobRolestring9 unique values
0 missing
JobSatisfactionnumeric4 unique values
0 missing
MaritalStatusstring3 unique values
0 missing
MonthlyIncomenumeric1349 unique values
0 missing
MonthlyRatenumeric1427 unique values
0 missing
NumCompaniesWorkednumeric10 unique values
0 missing
Over18string1 unique values
0 missing
OverTimestring2 unique values
0 missing
PercentSalaryHikenumeric15 unique values
0 missing
RelationshipSatisfactionnumeric4 unique values
0 missing
StandardHoursnumeric1 unique values
0 missing
StockOptionLevelnumeric4 unique values
0 missing
TotalWorkingYearsnumeric40 unique values
0 missing
TrainingTimesLastYearnumeric7 unique values
0 missing
WorkLifeBalancenumeric4 unique values
0 missing
YearsAtCompanynumeric37 unique values
0 missing
YearsInCurrentRolenumeric19 unique values
0 missing
YearsSinceLastPromotionnumeric16 unique values
0 missing
YearsWithCurrManagernumeric18 unique values
0 missing

19 properties

1470
Number of instances (rows) of the dataset.
34
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
25
Number of numeric attributes.
1
Number of nominal attributes.
2.94
Percentage of binary attributes.
0
Percentage of instances having missing values.
0.74
Average class difference between consecutive instances.
0
Percentage of missing values.
0.02
Number of attributes divided by the number of instances.
73.53
Percentage of numeric attributes.
84.63
Percentage of instances belonging to the most frequent class.
2.94
Percentage of nominal attributes.
1244
Number of instances belonging to the most frequent class.
15.37
Percentage of instances belonging to the least frequent class.
226
Number of instances belonging to the least frequent class.
1
Number of binary attributes.

0 tasks

Define a new task