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In this study, we find that COCOMO's estimates can be improved via WRAPPER- a feature subset selection method developed by the data mining community. Using data sets from the PROMISE repository, we show WRAPPER significantly and dramatically improves COCOMO's predictive power.<\/jats:p>","DOI":"10.1145\/1082983.1083171","type":"journal-article","created":{"date-parts":[[2005,11,7]],"date-time":"2005-11-07T19:28:32Z","timestamp":1131391712000},"page":"1-6","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["Feature subset selection can improve software cost estimation accuracy"],"prefix":"10.1145","volume":"30","author":[{"given":"Zhihao","family":"Chen","sequence":"first","affiliation":[{"name":"Univ. of Southern California"}]},{"given":"Tim","family":"Menzies","sequence":"additional","affiliation":[{"name":"Portland State Univ."}]},{"given":"Dan","family":"Port","sequence":"additional","affiliation":[{"name":"Univ. of Hawaii"}]},{"given":"Barry","family":"Boehm","sequence":"additional","affiliation":[{"name":"Univ. of Southern California"}]}],"member":"320","published-online":{"date-parts":[[2005,5,15]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/539425"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.5555\/557000"},{"key":"e_1_2_1_3_1","volume-title":"Estimating cost and schedule of software development and support","author":"P. 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