Abstract

Abstract: This paper recognizes the theory and practice of regressiontechniques for prediction of technical domain trends by using a converted dataset in ordinal data format. The data formats in technical proficiency and skilllevel provide a process for calculation of technical domain trends. Theconverted data set contains only a standardized ordinal data type which offersa process to measure rankings of technical skills. The primary design is basedon regression analysis from WEKA machine learning software. The technical domaintrends from Alumni Portal, KJSIEIT is used as our research setting. The datasources are alumni technical proficiency which included recently used skill andits level. The variables included in the data set were formed based ontechnical domain trends from the alumni profiles. Classifiers in WEKA were usedas algorithms to produce the outcomes. This learning showed that the results ofregression techniques can be used for the prediction of technical skills whichwould be trending in the future by using a dataset in standardized ordinal dataformat

Keywords:  regression techniques; machine learning; fundamentalanalysis; classifiers; linear regression, technical domain trends