data mining

Review the German Credit DataSet (Links to an external site.) (https://archive.ics.uci.edu/ml/datasets/Statlog+(German+Credit+Data)) in the attachment. It has 1,000 observations. Train, test and validate a neural network with the first 980 observations and however many neurons in the hidden layer as you like. Take a look at the data and remove a few attributes that you think do not help to determine the creditworthiness of a customer. The last column is whether a customer is actually “good” or “bad” (i.e., their credit rating). See if you can improve the accuracy by changing various parameters, such as the number of neurons, and the number of layers. After you train, test your holdout 20 samples and report the results using the method below. If your predictions are correct (good or bad) for each example, that counts as 0. If your prediction for a good customer is “bad” add 1 to your total. If your prediction for a bad customer is “good”, add 5 to your total. The lower the total the better your neural network. What you need to do. 1) Partition the data into training (980 data points) and holdout (last 20 data points) datasets. 2) Get the evaluation score of the 20 holdout data. Submission: a) Detailed Project Report that follows the example of the academic paper “Combining Feature Selection and Neural Network for Solving Classification Problem”. 1) Summary of your project 2) Introduction of applying data mining on the business problem (in this case, consumer credit card) 3) Discuss Data Mining Methods that are appropriate for your project problem. 4) TechnICAL Description of the German Credit Data Mining Process. You can choose any one of three data mining processes to describe your approaches. The following is based on the Cross-Industry Standard Process for Data Mining (CRISP-DM). a) Business Understanding b) Data Understanding c) Data Preparation d) Model Building Based on Neural Networks e) Testing and Evaluations (show all your screen plots and performance results). f) Deployment (potential concerns and issues when you apply your NN system to a real-life credit card company) 5) Description of Results and Analyze your experiment results and provide wisdom that you obtained from the project. 6) Conclusions

Don't use plagiarized sources. Get Your Custom Essay on
data mining
Get an essay WRITTEN FOR YOU, Plagiarism free, and by an EXPERT!
Order Essay
Homework Sharks
Order NOW For A 10% Discount!
Pages (550 words)
Approximate price: -

Our Advantages

Plagiarism Free Papers

All our papers are original and written from scratch. We will email you a plagiarism report alongside your completed paper once done.

Free Revisions

All papers are submitted ahead of time. We do this to allow you time to point out any area you would need revision on, and help you for free.

Title-page

A title page preceeds all your paper content. Here, you put all your personal information and this we give out for free.

Bibliography

Without a reference/bibliography page, any academic paper is incomplete and doesnt qualify for grading. We also offer this for free.

Originality & Security

At Homework Sharks, we take confidentiality seriously and all your personal information is stored safely and do not share it with third parties for any reasons whatsoever. Our work is original and we send plagiarism reports alongside every paper.

24/7 Customer Support

Our agents are online 24/7. Feel free to contact us through email or talk to our live agents.

Try it now!

Calculate the price of your order

We'll send you the first draft for approval by at
Total price:
$0.00

How it works?

Follow these simple steps to get your paper done

Place your order

Fill in the order form and provide all details of your assignment.

Proceed with the payment

Choose the payment system that suits you most.

Receive the final file

Once your paper is ready, we will email it to you.

Our Services

We work around the clock to see best customer experience.

Pricing

Flexible Pricing

Our prces are pocket friendly and you can do partial payments. When that is not enough, we have a free enquiry service.

Communication

Admission help & Client-Writer Contact

When you need to elaborate something further to your writer, we provide that button.

Deadlines

Paper Submission

We take deadlines seriously and our papers are submitted ahead of time. We are happy to assist you in case of any adjustments needed.

Reviews

Customer Feedback

Your feedback, good or bad is of great concern to us and we take it very seriously. We are, therefore, constantly adjusting our policies to ensure best customer/writer experience.