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TDM2151 Data Mining

Question

Answered

I only need the highlight Task 1  All group members must contribute to the technical aspects of the project. Each group can research a data mining project of your choice in Classification and Prediction only.  Choose the data set wisely and solve the problem. Your task for this assignment is to implement and evaluate Artificial Neural Networks, SVM, Adaptive Boosting, Random Forests. You also can explore other classifiers (please discuss with me first). Choose at least 3 classifiers. Data set: Parkinson's Disease, Depression Dataset, Early stage diabetes risk prediction dataset. Any other Malaysian data set available.  Task 2 Your task for this assignment is to select and evaluate clustering algorithms. Select two datasets from the UCI repository or use datasets of your own (you can use the same dataset you chose for assignment 1). Compare K Mean algorithm with hierarchical Clustering methos Your report should include Determine how you will measure the quality of the clusters produced.  Select two algorithms for each dataset and compare their results using your quality metrics. Description of the datasets and your quality metrics. Description of your experiment setup such as how you preprocessed the data (if any), how you chose the parameters for the selected algorithms (if any), and why. Present the experiment results. They should not be a simple copy-and-paste from the programming output, but rather presented in a tabular or chart format for easy comparison. Discuss the insights and conclusions from your experiments. For example, do different clustering methods make a difference in terms of quality or performance for the particular datasets you selected? And why?How data preprocessing might help?  Are there conditions or general types of datasets that will make certain algorithms more suitable than others? 

TDM2151 Data Mining

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Question: Create a program to meet given requirements within a deadline To pass this module assessment you must write a program that meets all the requirements set out in a "requirements specification". This models the real-world of software  engineering (S.E.) development. Ability to caref ...

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Task Instructions to students: 1. The assessment covers the topics in Units 3 and 4 of course materials.2. The total marks for Assignment 2 is 100 and contributes 25% to the total grade.3. Submit your assignment to the Online Assignment Submission System (OAS). Submission of assignments in hard co ...

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You are required to 1.Task 1: Requirement specification Understand the requirements, define the stakeholders of the system and present their functional and non-functional requirements. Construct you own requirement specification template for the project. List all identified use cases and write ...

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Aims The aim of the assignments is to introduce Decision Support Systems, fundamentals and applications. Students will analyse and evaluate key methods and algorithms of decision making and their potential applicability. Learning Outcomes Assessed 1.Analyse a problem statement and determine the re ...

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