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
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a decision support tool based on the Case Based Reasoning technique‚ meant to help physicians in the retrieval of past similar cases‚ able to provide a suggestion about the revision of diabetic patients’ therapy scheme. A case is defined as a set of features collected during a visit. A taxonomy of prototypical situations‚ or classes‚ has been formalized; a set of cases belonging to these classes has been stored into a relational data-base. For each input case‚ the system allows the physician
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Unit Unit 12 Internet Marketing in Business Assignment Title Marketing Online Issue Date Monday 10th March Hand In Date Friday 30th May Students Name Class Lecturer Neil Gow Assessment Criteria achieved P1 M1 D1 P2 M2 P3 P4 P5 P6 Learning Outcomes 1. Know what role internet marketing has within a modern marketing context 2. Understand the benefits of internet marketing to customers 3. Understand
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DATA MINING FOR POTENTIAL CUSTOMERS: East – West Airlines/Telcon Jermaine Paul 12/12/2013 BUSINESS PROBLEM East-West Airlines (EA) is entering into partnership with the cellular service provider‚ Telcon‚ by marketing their service through direct mail. In order to achieve this‚ EA dataset is provided to categorize their customers to identify which ones would be likely to purchase Telcon’s services through direct mail. If the accurate categorization is done the partnership will save
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2.1 Assuming that data mining techniques are to be used in the following cases‚ identify whether the task required is supervised or unsupervised learning. a. Supervised-Deciding whether to issue a loan to an applicant based on demographic and financial data (with reference to a database of similar data on prior customers). b. Unsupervised-In an online bookstore‚ making recommendations to customers concerning additional items to buy based on the buying patterns in prior transactions. c. Supervised-Identifying
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Data Mining: A Tool for the Enhancement of Banking Sector Shipra Kalra; Rachika Gupta kalra.shipra87@gmail.com; guptarachika@yahoo.co.in Lecturer‚ Chanderprabhu Jain College of Higher Studies and School of Law‚ Sector A-8‚ Narela‚ Delhi-110040 Abstract Data mining is emerging as a very useful tool for providing valuable information from large databases and enabling managers and business executives to make hard core decisions in a much easier and effective manner. It is a process of analyzing the
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Programme – Term IV – AY 20012-13 Business Intelligence And Data Mining Group Assignment on NGO Donations Maximization Abstract The problem is associated to devising a strategy to maximize the profits from a Direct Marketing Campaign to a selected group of customers while minimizing costs . The exercise requires the use of Business Intelligence tools and techniques to build a model ‚ trained and tested on the historical data for the last year’s donation raising campaign . From this
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Semester 1‚ 2012 Comparison of Advertising Techniques of American TV Commercials of the 1950s and Today The 1950s in America were the “Golden Age of Television” (‘The Golden Age of Television’‚ 2009). After the Second World War ended‚ all the money people had saved over the last four years was just waiting to be spent. The result was 50 million television sets by 1960 in the United States (Miller and Novak‚ 1977‚ p.344). The 1950s were a decade of economic optimism which resulted in greater
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the Study 6. Motivation REVIEW OF RELATED LITERATURE AND STUDIES 1. Review of Related Literature 2. Review of Related Studies 3. Conceptual Framework 4. Operational Definition of Terms METHODOLOGY 1. Methods of Research 2. Data Gathering Techniques 3. Statistical Treatment of Data (optional) SYSTEM PRESENTATION A. Existing System 1. Company Background 2. Description of the System 3. Process Flow of the System 4. Analysis of the System B. Proposed System 1. Description of the System 2. Objectives of
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the internet channel. Nowadays‚ consumers have the tendency to shop online. Thus‚ a good internet marketing plan would help an organization to position their product or service in such a manner that the target audience can be reached. Yet‚ there are some difficulties that companies and consumers face where the point is for that research. This research points out some major limitations faced by the internet nowadays and on which further research is required. INTRODUCTION Marketing is an
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