Suppose you are tasked with developing a machine learning model to predict whether a customer will churn (leave) a subscription service based on their usage patterns and demographic information. What steps would you take to address this problem?
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- TESTING YOUR UNDERSTANDING Exercise 3-1. Consider the scenario described at the beginning of this chapter: When parents call to say that children are sick, we have to let their classroom teachers know, and if it's sports day and the child is on a school team, the sports teacher might have to sort out substitutes. Then we need to count up all the days missed to put on the child's report. The Department of Education needs the totals each term, too. Run through the steps in the summary section and sketch some use cases and an initial data model. Assume that the main objectives are to record the absences for the classroom teacher, for school reports, and for statistics given to the Department of Education.In what ways are prescriptive models different from predictive models?Suppose, as manager of a chain of stores, you would like to use sales transactional data to analyze the effectiveness of your store's advertisements: In particular, you would like to study how specific factors influence the effectiveness of advertisements that announce a particular category of items on sale. The factors to study are: the region in which customers live, and the day-of-the-week, and time-of-the-day of the ads. Discuss how to design an efficient method to mine the transaction data sets and explain how multidimensional and multilevel mining methods can help you derive a good solution.
- What skills are required to work with predictive models?In your mind's eye, what does an email seem like? In the case of email, the journey begins and ends in the same spot. Keep track of your findings. If there should be no distinctions, why are there any? Look at how the levels of detail (or lack thereof) in the models vary.What abilities do predictive modelers need?
- How can log data be used to train machine learning models?You are developing a simulation model of a service system and are trying to create an input model of the customer arrival Process, You have the following four observations of the process of interest [86, 24,9, 50] and you are considering either an exponential distributionor a uniform distribution for the model. Using the data to estimate any necessary distribution Parameters, write the steps to plot Q-Q plots for both uniform and exponential distribution. Write the steps clearly. Thanks.You have four various machine learning algorithms to pick from for supervised learning on a dataset. Describe any four factors you would use to help you decide which one to employ for a certain task.