Data
ERA

ERA

active ARFF Publicly available Visibility: public Uploaded 04-10-2014 by Joaquin Vanschoren
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Author: Source: Unknown - Date unknown Please cite: 1. Title: Employee Rejection\Acceptance (Orinal ERA) 2. Source Informaion: Donor: Arie Ben David MIS, Dept. of Technology Management Holon Academic Inst. of Technology 52 Golomb St. Holon 58102 Israel abendav@hait.ac.il Owner: Yoav Ganzah Business Administration School Tel Aviv Univerity Ramat Aviv 69978 Israel 3. Past Usage: 4. Relevant Information The ERA data set was originally gathered during an academic decision-making experiment aiming at determining which are the most important qualities of candidates for a certain type of jobs. Unlike the ESL data set (enclosed) which was collected from expert recruiters, this data set was collected during a MBA academic course. The input in the data set are features of a candidates such as past experience, verbal skills, etc., and the output is the subjective judgment of a decision-maker to which degree he or she tends to accept the applicant to the job or to reject him altogether (the lowest score means total tendency to reject an applicant and vice versa). 5. Number of Instances: 1000 6. Number of Attributes: 4 input, 1 output. 7. Attribute Information: All input and output values are ORDINAL. 8. Missing Attribute Values: None. 9. Class Distribution:

5 features

out1 (target)numeric9 unique values
0 missing
in1numeric13 unique values
0 missing
in2numeric15 unique values
0 missing
in3numeric13 unique values
0 missing
in4numeric14 unique values
0 missing

19 properties

1000
Number of instances (rows) of the dataset.
5
Number of attributes (columns) of the dataset.
0
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.
5
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
-1.19
Average class difference between consecutive instances.
100
Percentage of numeric attributes.
0.01
Number of attributes divided by the number of instances.
0
Percentage of nominal attributes.
Percentage of instances belonging to the most frequent class.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.

14 tasks

0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: out1
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: mean_absolute_error - target_feature: out1
0 runs - estimation_procedure: 33% Holdout set - target_feature: out1
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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