Data Mining Based Predictions for Employees Skill Enhancement Using Pro- Skill-Improvement Program and Performance Using Classifier Scheme Algorithm

Akhilesh k. Sharma, Dr. Kamaljit Lakhtaria, Santosh Vishwakarma


In the research paper we proposed extraction of knowledge significant for predicting the skill development program needs of
newly-hired employees, in order to enhance employees inherent potentials using classifier scheme for data mining technique. In
discovering significant models needed for predictive analysis, the Cross Industry Standard Process for Data Mining (CRISP-DM) was
employed. Results show that professional skill development programs are needed in order to prepare employees to perform their tasks
more efficiently.The knowledge flow model of the Opensource tool is also used to frame the elements. The tool from Waikato
university is used for the framing of the model adapted.


Keywords: Data mining, skill development, Classifier, CRISP-DM,KDD, Bayes Net, JRIP

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