0 ARFF 0 active humans_numeric Public ABS((TotalEstimates-TotalActual)/TotalActual) 2014-01-06T22:57:28Z 2014-01-07T01:52:02Z set target feature **Author**: **Source**: Unknown - Date unknown **Please cite**: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 1. Title: Assessing the Reliability of a Human Estimator %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% This is a PROMISE Software Engineering Repository data set made publicly available in order to encourage repeatable, verifiable, refutable, and/or improvable predictive models of software engineering. If you publish material based on PROMISE data sets then, please follow the acknowledgment guidelines posted on the PROMISE repository web page http://promisedata.org/repository . %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% (c) 2007 : Gary Boetticher : boetticher AT uhcl DOT edu Phone: +1 (281) 283 8305 This data set is distributed under the Creative Commons Attribution-Share Alike 3.0 License http://creativecommons.org/licenses/by-sa/3.0/ You are free: * to Share -- copy, distribute and transmit the work * to Remix -- to adapt the work Under the following conditions: Attribution. You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). Share Alike. If you alter, transform, or build upon this work, you may distribute the resulting work only under the same, similar or a compatible license. * For any reuse or distribution, you must make clear to others the license terms of this work. * Any of the above conditions can be waived if you get permission from the copyright holder. * Apart from the remix rights granted under this license, nothing in this license impairs or restricts the author's moral rights. 2. Sources (a) Creator: Gary D. Boetticher (b) Date: February 20, 2007 (c) Contact: boetticher AT uhcl DOT edu Phone: +1 (281) 283 8305 3. Donor: Gary D. Boetticher 4. Past Usage: This data was used for: Boetticher, G., Lokhandwala, N., James C. Helm, Understanding the Human Estimator, Second International Predictive Models in Software Engineering (PROMISE) Workshop co-located at the 22nd IEEE International Conference on Software Maintenance, Philadelphia, PA, September, 2006. More information is available at http://nas.cl.uh.edu/boetticher/research.html Since PROMISE 2006, the data set expanded by about 50 percent. The additional tuples allowed us to divide the data into 3 major categories. Those who severely underestimate (first 25 tuples). Those who accurately estimate (next 25 tuples). And those who severely overestimate (last 25 tuples). The PROMISE 2007 experiments compare the underestimators with the accurate estimators and the overestimators with the accurate estimators. 5. Number of Instances: 75 6. Number of Attributes: 14 independent variables and 1 dependent variable 7. Attribute Information: Numeric Degree: This attribute refers to the level of education of the participant. 2=High School, 3=Bachelors, 4=Masters,5=Ph.D. TechUGCourses: This refers to the number of technical undergraduate courses that the participant has taken. TechGCourses: This refers to the number of technical graduate courses that the participant has taken. MgmtUGCourses: This refers to the number of management undergraduate courses that the participant has taken. MgmtGCourses: This refers to the number of management graduate courses that the participant has taken. Total Workshops: This refers to the total number of workshops that the participant has attended. Total Conferences: This refers to the total number of conferences that the participant has attended. TotalLangExp: This refers to the total number of languages and experience in those languages that the participant has. Hardware Proj Mgmt Exp: This corresponds to the total amount of time that the respondant has been estimating hardware projects. Software Proj Mgmt Exp: This corresponds to the total amount of time that the respondant has been estimating software projects. No Of Hardware Proj Estimated: This refers to the total number of hardware projects that the participant has estimated. No Of Software Proj Estimated: This refers to the total number of software projects that the participant has estimated. Domain Exp: The domain experience refers to how much experience the participant has in the oil and gas industry. Procurement Industry Exp: The procurement industry experience refers to the amount of time, in years, that the participant has regarding procurement. ABS((TotalEstimates-TotalActual)/TotalActual): This is the class variable. It represents the overall relative error for the participant's estimates. public https://www.openml.org/data/download/53941/humans_numeric.arff 0 humans_numeric 1