will win is 60% and above.” Null Hypothesis “If X makes the first move then the probability of the player with X will win is less than 60%.” Data Collection and Preparation To prove or refute the hypothesis‚ data has to be collected. As we all know this step requires a great amount of time and effort. Also in order to build an effective model a data mining algorithm must be presented with a few hundred or few thousands relevant/applicable records. As mentioned above there are thousands of winning
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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
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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
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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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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 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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United Cereal: Lora Brill’s Eurobrand Challenge Introduction: The case is focusing on European division of a giant multinational breakfast food company‚ which describes a launch decision for a new cereal product. United Cereal (UC) was established in 1910 by Jed Thomas. It was known in the industry‚ eventually diversified into snack foods‚ dairy products. By 2010 UC was a $9 billion business‚ but the breakfast cereals still accounted for one-third of its revenues. As the breakfast cereal trend
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Data Mining Project on IMDB website ABSTRACT The Internet Movie Database (IMDb) is an online database of information related to movies‚ television shows‚ stars‚ etc. We chose to do our project from 2008 to 2011 year’s movie database. We extracted data like Movie‚ Director‚ Star‚ Image Url‚ Studio from the IMDb website. For this extraction of data we used a tool named Mozenda. After the data extraction‚ the data was analyzed. For a particular star‚ his/her movie‚ director‚ studio with whom the
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With the proposed Canadian Keystone XL Pipeline in the midst of approval‚ Americans can look forward to the potential of job growth and less dependencies upon foreign imports. The project proposes a 1‚179 mile‚ 36 inch-diameter crude oil pipe. Crude oil a petroleum product is a liquid composed of hydrocarbons‚ organic compounds and small amounts of metal. It is created through the heating and compression of organic materials‚ over a long time period. The pipeline would start in the town of Hardisty
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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 find similar situations that already took place in the past‚ both for the same patient and for different ones. The reasoning process consists of two steps: 1) finding the classes to which the
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