| Type of Material: | Thesis |
| Title: | An enhanced approach for prediction of software project success using fuzzy cmeans genetic algorithm and random forest in software industry |
| Researcher: | Pushpavathi T P |
| Guide: | Ramaswamy V |
| Publisher: | Jain University |
| Place: | Bengaluru |
| Language: | English |
| Dissertation/Thesis Note: | PhD |
| Fulltext: | Shodhganga |
| 000 | 00000ntm a2200000ua 4500 | |
| 001 | 339844 | |
| 003 | IN-AhILN | |
| 005 | 2018-08-14 05:41:29 | |
| 008 | __ | 180814t####||||ii#||||g|m||||||||||eng|| |
| 035 | __ | |a(IN-AhILN)th_339844 |
| 040 | __ | |aJAIN_560027|dIN-AhILN |
| 041 | __ | |aeng |
| 100 | __ | |aPushpavathi T P|eResearcher |
| 245 | __ | |aAn enhanced approach for prediction of software project success using fuzzy cmeans genetic algorithm and random forest in software industry |
| 260 | __ | |aBengaluru|bJain University |
| 502 | __ | |bPhD |
| 520 | __ | |aSuccess of any software organization depends on total customer satisfaction which in turn depends on the development of quality software Software Engineering methodology enables the production of quality software |
| 700 | __ | |aRamaswamy V|eGuide |
| 856 | __ | |uhttp://shodhganga.inflibnet.ac.in/handle/10603/92371|yShodhganga |
| 905 | __ | |anotification |
User Feedback Comes Under This section.