arulesCBA: Classification for Factor and Transactional Data Sets Using Association Rules
نویسنده
چکیده
This paper presents an R package, arulesCBA, which uses association rules mined with the apriori algorithm from arules to build a classifier for discrete or transactional data sets. The package also provides an interface to use an association-rule classifier to predict classes for new data entries. The classification algorithm implemented in arulesCBA performs competitively when compared to existing discrete classification algorithms.
منابع مشابه
On Mining Fuzzy Classification Rules for Imbalanced Data
Fuzzy rule-based classification system (FRBCS) is a popular machine learning technique for classification purposes. One of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. However many cases the minority classes are more important than the majority ones. In this paper, we have extended ...
متن کاملOn Mining Fuzzy Classification Rules for Imbalanced Data
Fuzzy rule-based classification system (FRBCS) is a popular machine learning technique for classification purposes. One of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. However many cases the minority classes are more important than the majority ones. In this paper, we have extended ...
متن کاملUsing a Data Mining Tool and FP-Growth Algorithm Application for Extraction of the Rules in two Different Dataset (TECHNICAL NOTE)
In this paper, we want to improve association rules in order to be used in recommenders. Recommender systems present a method to create the personalized offers. One of the most important types of recommender systems is the collaborative filtering that deals with data mining in user information and offering them the appropriate item. Among the data mining methods, finding frequent item sets and ...
متن کاملDiscovering Association Rules in Incomplete Transactional Databases
The problem of incomplete data in the data mining is well known. In the literature many solutions to deal with missing values in various knowledge discovery tasks were presented and discussed. In the area of association rules the problem was presented mainly in the context of relational data. However, the methods proposed for incomplete relational database can not be easily adapted to incomplet...
متن کاملApplying a decision support system for accident analysis by using data mining approach: A case study on one of the Iranian manufactures
Uncertain and stochastic states have been always taken into consideration in the fields of risk management and accident, like other fields of industrial engineering, and have made decision making difficult and complicated for managers in corrective action selection and control measure approach. In this research, huge data sets of the accidents of a manufacturing and industrial unit have been st...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2017