INFO411 - Data Mining and Knowledege Discovery - Visualization and Clustering Techniques - Computer Science Assignment Help

Assignment Task:

Purpose of this task:

You are to start with an analysis of the general properties of this dataset by using suitable visualization and clustering techniques (i.e. Such as those introduced during the lectures), and you are to obtain an insight into the degree of difficulty of this prediction task. Then you are to design and deploy an appropriate supervised prediction model (i.e. MLP) to obtain a prediction of customer ratings. 
 
Question 1:Analyse the general properties of the dataset and obtain an insight into the difficulty of the prediction task. Create a statistical analysis of the attributes and their values, then list 5 of the most interesting (most valuable) attributes. Explain the reasons that make these attributes interesting. Note: A set of R-script files are provided with this assignment. The scripts provided will allow you to produce some first results. However, virtually none of the parameters used in these scripts are suitable for obtaining a good insight into the general properties of the given dataset. Hence your task is to modify the scripts such that informative results can be obtained from which conclusions about the learning problem can be made. Note that finding a good set of parameters is often very time consuming in data mining. An additional challange is to make a correct interpretation of the results. 
 
This is what you need to do: Find a good set of parameters (i.e. Through a trial and error approach), obtain informative results then offer an interpretation of the results. Write down your approach to conducting the experiments, explain your results, and offer a comprehensive interpretation of the results. Do not forget that you are also to provide an insight into the degree of difficulty of this learning problem.

Question 2:Deploy a prediction model to predict the credit worthiness of customers which have not yet been assessed. The prediction capabilities of the MLP in the lab of “Classification” was very poor. Your task is to: a.) Describe a valid strategy that maximises the accuracy of predicting the credit rating. Explain why your strategy can be expected to maximise the prediction capabilities. b.) Use your strategy to train MLP(s) then report your results. Give an interpretation of your results. What is the best classification accuracy (expressed in % of correctly classified data) that you can obtain for data that were not used during training (i.e. The test set)? 

This INFO411 - Computer Science Assignment has been solved by our Computer Science Experts at My Uni Paper. Our Assignment Writing Experts are efficient to provide a fresh solution to this question. We are serving more than 10000+ Students in Australia, UK & US by helping them to score HD in their academics. Our Experts are well trained to follow all marking rubrics & referencing style.

Be it a used or new solution, the quality of the work submitted by our assignment experts remains unhampered. You may continue to expect the same or even better quality with the used and new assignment solution files respectively. There’s one thing to be noticed that you could choose one between the two and acquire an HD either way. You could choose a new assignment solution file to get yourself an exclusive, plagiarism (with free Turnitin file), expert quality assignment or order an old solution file that was considered worthy of the highest distinction.