Precisely, the creation of research problem, formulation of research hypothesis, conducting literature review, data collection, choice of suitable parametric or non-parametric statistical technique for evaluating data, extent the impact of published research at journal-level, article-level, and author-level and introducing the Data mining tool WEKA. The practice on WEKA includes Data Acquisition/ PreProcessing, Algorithm Learning, Result Analysis (Result Interpretation) and Decision making.

Objectives:

The participants can be able to describe the research problem, evolving an approach to research problem and choice of suitable research design. To experience the formulation and testing of hypothesis based on the nature of research. To understand the journal publication metrics at author level, article level and journal level. To analyze the research data by introducing the data mining tool “WEKA”. To experience “WEKA” in research.

Prerequisites

• Basic understanding of machine learning algorithms