Search Results - subject:"Data mining."

COMPARISON OF APRIORI AND FP-GROWTH ALGORITHMS ON DETERMINATION OF ASSOCIATION RULES IN AUTHORIZED AUTOMOBILE SERVICE CENTRES

Erpolat, Semra - In: Anadolu University Journal of Social Sciences 12 (2012) 2, pp. 137-146

Data Mining is used to describe the totality of techniques which aim to find the unexplored patterns in a set of data …. The purpose of data mining is to create models of decision-making devoted to estimations of future behavior based on …

Persistent link: https://www.econbiz.de/10010562486

Using GARCH-IN-mean model to investigate volatility and persistence at different frequencies for Bucharest Stock Exchange during 1997-2012

PANAIT, Iulian; SLAVESCU, Ecaterina Oana - In: Theoretical and Applied Economics XVIII(2012) (2012) 8(573), pp. 63-84

In our paper we use data mining to compare the volatility structure of high (daily) and low (weekly, monthly …

Persistent link: https://www.econbiz.de/10010568138

South African stock return predictability in the context data mining: The role of financial variables and international stock returns

Gupta, Rangan; Modise, Mampho P. - In: Economic Modelling 29 (2012) 3, pp. 908-916

power properties were utilised. To guard against data mining, a bootstrap procedure was employed for calculating the … and long run horizons. When accounting for data mining, the maximal out-of-sample test statistics become insignificant … from 6-months onward suggesting that the evidence of the out-of-sample predictability at longer horizons is due to data …

Persistent link: https://www.econbiz.de/10010573379

Gaining insight into student satisfaction using comprehensible data mining techniques

Dejaeger, Karel; Goethals, Frank; Giangreco, Antonio; … - In: European Journal of Operational Research 218 (2012) 2, pp. 548-562

, we address this issue by investigating the applicability of different data mining techniques to identify the main drivers … least equally important as model performance. It is found that data mining techniques are able to select a surprisingly …

Persistent link: https://www.econbiz.de/10010574137

Multicriteria variable selection for classification of production batches

Anzanello, Michel J.; Albin, Susan L.; Chaovalitwongse, … - In: European Journal of Operational Research 218 (2012) 1, pp. 97-105

In many industrial processes hundreds of noisy and correlated process variables are collected for monitoring and control purposes. The goal is often to correctly classify production batches into classes, such as good or failed, based on the process variables. We propose a method for selecting...

Persistent link: https://www.econbiz.de/10010574140

Mining axiomatic fuzzy set association rules for classification problems

Wang, Xin; Liu, Xiaodong; Pedrycz, Witold; Zhu, Xiaolei; … - In: European Journal of Operational Research 218 (2012) 1, pp. 202-210

In this paper, we propose a novel method to mine association rules for classification problems namely AFSRC (AFS association rules for classification) realized in the framework of the axiomatic fuzzy set (AFS) theory. This model provides a simple and efficient rule generation mechanism. It can...

Persistent link: https://www.econbiz.de/10010574150

New insights into churn prediction in the telecommunication sector: A profit driven data mining approach

Verbeke, Wouter; Dejaeger, Karel; Martens, David; Hur, Joon - In: European Journal of Operational Research 218 (2012) 1, pp. 211-229

Customer churn prediction models aim to indicate the customers with the highest propensity to attrite, allowing to improve the efficiency of customer retention campaigns and to reduce the costs associated with churn. Although cost reduction is their prime objective, churn prediction models are...

Persistent link: https://www.econbiz.de/10010574169

Normalised support: a virtual angle of measurement of 'interestingness'

Alsabhan, Waleed - In: International Journal of Data Analysis Techniques and … 4 (2012) 1, pp. 101-114

Association rule mining is applied to large databases to identify product associations. In the resulting large number of rules, interestingness is difficult to determine. Researchers have defined various measures of 'interestingness' such as support, confidence, lift and gain. Support is the...

Persistent link: https://www.econbiz.de/10010669740

A data warehousing and data mining approach for analysis and forecast of cloudburst events using OLAP-based data hypercube

Pabreja, Kavita; Datta, Rattan K. - In: International Journal of Data Analysis Techniques and … 4 (2012) 1, pp. 57-82

The multidimensional data model can be effectively utilised for analysing huge and detailed meteorological datasets forecasted by numerical weather prediction (NWP) model. The model cannot predict any weather event directly. The output products of model are interpreted by man-machine mix to...

Persistent link: https://www.econbiz.de/10010669741

Cluster Analysis of Smart Metering Data

Flath, Christoph; Nicolay, David; Conte, Tobias; … - In: Business & Information Systems Engineering 4 (2012) 1, pp. 31-39

The introduction of smart meter technology is a great challenge for the German energy industry. It requires not only large investments in the communication and metering infrastructure, but also a redesign of traditional business processes. The newly incurring costs cannot be fully passed on to...

Persistent link: https://www.econbiz.de/10010680783