• Shilpa
• Tarandeep Kaur

Abstract: In this contemporary era, Industry producing large amount of data due to which they deal with data mining. Data Mining techniques are used to discover different factors affecting a dataset performance. The main aim of this paper is to identify the associativity between the attributes of the dataset. Such as Naïve Bayes and Linear Regression. The attributes considered for this analysis were CGPA, score based on individual course, aggregate attendance, Continuous assessment marks, mid-term marks and end-term marks. The model is used to predict the associativity so that the instructors are able to classify the rules and take the corrective actions.

Keywords: Associativity, Data Mining, Dataset, FP Growth

"Data Analysis using Association Rule in Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 11, page no.316-319, November 2018, Available :http://www.jetir.org/papers/JETIRDS06050.pdf

"Data Analysis using Association Rule in Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 11, page no. pp316-319, November 2018, Available at : http://www.jetir.org/papers/JETIRDS06050.pdf