| Updated in 6/21/2018 8:52:34 AM |
Viewed: 419 times |
(Document) |
77-86
Exploratory data analysis of software requirements using statistics and kohonen’s self-organizing map
R Štrba
,
K Štrbová
,
I Vondrák
,
D Ježek
,
S Štolfa
ABSTRACT
Many factors affect the success of prediction using Machine-Learning on given task. The quality of provided data is one of the key factors which influence accuracy of Machine-Learning (ML) and Artificial Intelligence (AI) algorithms. The main goal of this research is to explore data, choose the right parameters and remove noisy items before usage of ML or AI. This research provides results of exploratory data analysis of software requirements collected from Software Company. Presented results help identify general patterns in the dataset of software requirements for future prediction purposes. © 2018, Springer International Publishing AG.
Notes
Export Date: 11 December 2017