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Question: hello this is for datascience applications below is a question...

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Hello, this is for Datascience Applications. Below is a question from the textbook “fundamentals of machine learning for predictive data analytics,” chapter 3, ISBN: 978-0-262-02944-5.

If you use excel please include all formulas you use, for example “ =quartile(table1(income),0.25) “ , I ask this because I am new to excel and I could really use that as guidance, so please include everything. Please include any chart you may make too please.

Thank you so very much!

Below is a picture of the textbook and the exercise 4 from chapter 3.

JoHN D. KELLEHER BRIAN MAC NAMEE AoIFE DARCY FUNDAMENTALS OF MACHINE LEARNING FOR PREDICTIVE DATA ANALYTICS ALGORITHMS, WORKED EXAMPLES, AND CASE STUDIES

4. The following data visualizations are based on the channel prediction dataset given in Question 3. Each visualization illustrates the relationship between a descriptive feature and the target feature, PREFCHANNEL. Each Each o four plots: one plot of descriptive feature values in the entire dataset, and three plots illustrating the distribution of the descriptive feature values for each level of the target Discuss the strength of the relationships shown in each visualizations.

Note for table A, the y-axis is “density” and the x-axis is “age.”

For table B, the y-axis is “density” and the x-axis is “gender” where the left bar is female and the right bar is male.

For table C, the y-axis is “density” and the x-axis is “Loc” where the left bar is Rural and the right bar is Urban.

a. The visualization below illustrates the relationship between the contin- uous feature AGE and the target feature, PREFCHANNEL b. The visualization below illustrates the relationship between the categor- ical feature GENDER and the target feature PREFCHANNEL
108 Chapter 3 Data Exploration categor- c. The visualization below illustrates the relationship between the ca ical feature LOC and the target feature, PREFCHANNEL PrefChannel Emal PrefChannel SMS PretChannel Phone
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