Use Microsoft Word to create a concise Project Proposal for Knowledge Discovery in Databases, 1-2 single-spaced pages in length, containing the following sections:
This section provides an overview of your project and then makes a statement of proposal.
Define the area of research that is the focus of your project; define the context and the knowledge base the research is based on.
This section concisely states the goals of your project. Examples of goals are listed in the KDD Cup pages (see examples onhttp://www.kdnuggets.com/datasets/kddcup.html). It should include the questions the project intends to answer. Describe the problem(s) to be solved, as a set of general questions the data mining system will provide insight into, and the intended users.
List the size of the dataset of your choice by specify the number of attributes, domain of attributes, number of rows, percentage of missing values, and format. Just a reminder, you should choice a dataset from the UCI Knowledge Discovery in Databases Archive,http://kdd.ics.uci.edu/.
Briefly describe the data mining tools you plan to use (SAS, WEKA, Clementine …) and the approaches you will use (association rules, classification J4.8, evolution analysis…). KDDnuggets home (http://www.kdnuggets.com/software/index.html) contains a list of software with brief explanations of their functions. Some software are free and some do not. I suggest that you utilize WEKA as it is a free tool and it supports data preprocessing, classification, association, and clustering.
The UCI Knowledge Discovery in Databases Archive, http://kdd.ics.uci.edu/summary.task.type.html, classifies datasets based on mining task such as Classification, Clustering … etc. You are suggested to reference your dataset’ task type to decide your project approach.
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