Department of Computer Science Database and Data Mining‚ COS 514 Dr. Chi Shen Homework No. 8‚ Chapter 13‚ Aklilu Shiketa Q13. 3 Cosmetic Purchases Consider the following Data on Cosmetics Purchases in Binary Matrix Form a) Select several values in the matrix and explain their meaning. Value Cell Meaning 0 For example‚ Row 1‚ Column2 At transaction #1 bag was not purchased. (shows absence of Bag in the transaction) 1 Row 10‚ column (2 and 3) “If a Bag is purchased‚ a Blush is also purchased
Premium Data mining Cosmetics Logic
Henceforth‚ by applying Data Mining (DM) algorithms for Business Intelligence‚ it is possible to automate the analysis process‚ thus comes the ability to extract patterns and other important information from the data set. Understanding the reason why Data Mining is needed in Business Intelligence and also the process‚ applications and different tasks that Data Mining provides for Business Intelligence purposes is the main subject area in this essay. Data mining process is also commonly referred
Premium Data mining
Use of Data Mining in Fraud Detection Focus on ACL Hofstra University Abstract This paper explore how business data mining software are used in fraud detection. In the paper‚ we discuss the fraud‚ fraud types and cost of fraud. In order to reduce the cost of fraud‚ companies can use data mining to detect the fraud. There are two methods: focus on all transaction data and focus on particular risks. There are several data mining software on the market‚ we introduce seven
Premium Data mining Data analysis Fraud
“Energy and Efficiency analysis of 210MWe coal base Thermal Power Plant with running parameters” Goutam Khankari‚DVC‚Kolkata. INTRODUCTION Power projects are essentially capital intensive. Not only they involve a highly initial cost which is around Rs. 4.5 to 5.0 crores per MW for coal-based plants but also huge operation cost. The running expenses of a 210MW thermal power station may range around thirty crores every month and usually about 80% of this goes towards the fuel cost. Not only fuel
Premium Coal Chemical engineering Thermal power station
R and Data Mining: Examples and Case Studies 1 Yanchang Zhao yanchang@rdatamining.com http://www.RDataMining.com April 26‚ 2013 1 ➞2012-2013 Yanchang Zhao. Published by Elsevier in December 2012. All rights reserved. Messages from the Author Case studies: The case studies are not included in this oneline version. They are reserved exclusively for a book version. Latest version: The latest online version is available at http://www.rdatamining.com. See the website also for an R Reference Card
Premium Data mining
A data mining approach to analysis and prediction of movie ratings M. Saraee‚ S. White & J. Eccleston University of Salford‚ England Abstract This paper details our analysis of the Internet Movie Database (IMDb)‚ a free‚ user-maintained‚ online resource of production details for over 390‚000 movies‚ television series and video games‚ which contains information such as title‚ genre‚ box-office taking‚ cast credits and user ’s ratings. We gather a series of interesting facts and relationships
Premium Actor Data mining Film
Overview: Chapter 2 Data Mining for Business Intelligence Shmueli‚ Patel & Bruce Core Ideas in Data Mining Classification Prediction Association Rules Data Reduction Data Visualization and exploration Two types of methods: Supervised and Unsupervised learning Supervised Learning Goal: Predict a single “target” or “outcome” variable Training data from which the algorithm “learns” – value of the outcome of interest is known Apply to test data where value is not known and will be predicted
Premium Data analysis Data mining
OIL PRICES PER BARREL ON THE OPERATIONS AND FUNCTIONING OF THE MINING INDUSTRY IN Research Proposal Candidate: Faculty: Economics and Administrative Sciences Instructor: Cyprus International University‚ Haspolat‚ Lefcosa‚ Turkish Republic of Northern Cyprus. Aim: The aim of this study is to investigate whether or not an increase in the price charged for oil per barrel will have an impact on the overall functioning of the mining industry and the operations carried out there. Hypothesis: There
Premium Peak oil Petroleum OPEC
and Retaining Business in the Australian Mining Equipment Sector‚ 2014 On 16th June 2014 Synopsis The survey primarily assessed heavy mobile equipment‚ however respondents were also asked about their practices and preferences in areas such as mining software‚ technology‚ and maintenance. Areas of analysis include: Customer priorities when buying mining equipment‚ with ratings of the importance of 16 separate factors for customers when choosing mining equipment‚ including cost factors‚ supplier
Premium Customer satisfaction Management Market research
Building Data Mining Applications for CRM Introduction This overview provides a description of some of the most common data mining algorithms in use today. We have broken the discussion into two sections‚ each with a specific theme: • Classical Techniques: Statistics‚ Neighborhoods and Clustering • Next Generation Techniques: Trees‚ Networks and Rules Each section will describe a number of data mining algorithms at a high level‚ focusing on the "big picture" so that the reader will
Premium Data mining Regression analysis