Questions On Business Intelligence And The Test Partition

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Question #1 – As we are just beginning the course, what are your definitions of: • Business Intelligence: Business intelligence is a program that coordinates the best combinations of data in sales to achieve maximum profits. • Business Analytics: Analyzing the business modules for better profitable outcomes. • Data Mining: Process of extracting data and matching it to the desired business modules. Shmueli Chapter #2 Problems 2.2, 2.3, 2.4, 2.5, 2.6, and 2.10 Problem 2.2: Describe the difference in roles assumed by the validation partition and the test partition. Answer: According to Shmueli ‘Validation Partition- This partition (sometimes called the test partition) is used to assess the performance of each model so that you can…show more content…
• There aren’t enough responses with 0 in them (most of them are 1s) Problem 2.4: Consider the sample from a bank database shown in Figure 2.14; it was selected randomly from a larger database to be the training set. Personal Loan indicates whether a solicitation for a personal loan was accepted and is the response variable. A campaign is planned for a similar solicitation in the future, and the bank is looking for a model that will identify likely responders. Examine the data carefully and indicate what your next step would be. Answer: Our next step ought to be to get more information where the personal loan was acknowledged. This sample data has all rejected personal loans, as assuming 0 stands for rejection. Problem 2.5: Using the concept of overfitting, explain why when a model is fit to training data, zero error with those data is not necessarily good. Answer: Zero error in a training data in most cases shows that the model has fit random noise in the training data as well. This implies that the model won 't sum up well for new or unknown data. Problem 2.6: In fitting a model to classify prospects as purchasers or non-purchasers, a certain company drew the training data from internal data that include demographic and purchase information. Future data to be classified will be lists purchased from other sources, with demographic (but not purchase) data included. It was found that “refund issued” was a useful

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