Category | Assignment | Subject | computer science |
---|---|---|---|
University | ____ | Module Title | CIS111-6: Intelligent Systems and Data Mining |
Assignment Title: | Task 2: Advanced Data Mining Techniques for Direct Marketing Campaigns |
Task 2 count words: | 2500 |
Students will develop one or more Advanced Data Mining (ADM) techniques for saving thecost of a direct marketing campaign by reducing false positive (wasted call) and falsenegative (missed customer) predictions. Students could consider the scenario of theAssignment 1 to optimise a given marketing campaign with ADM techniques. Examples ofADM techniques such as Artificial Neural Networks and Gradient Boosting Machines will begiven in related tutorials.
To design a solution, students will apply ADM techniques discussed in lectures and will use related packages available on the R repository. Using the ADM techniques, students will run individual experiments to find a solution providing the best accuracy of predicting client profiles on the bank marketing used for designing a solution to the Assignment 1. The useof this data allows students to compare different DM techniques in terms of prediction accuracy.
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Order Non Plagiarized AssignmentDownload the Bank marketing data (.csv) required for individual experiments.
Each solution will be evaluated in terms of the prediction accuracy determining theefficiency of the marketing campaign. All submissions are made via BREO. A template canbe used for reports. Exclude paste© fragments to avoid plagiarism.
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