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You're reading from  Data Science Projects with Python - Second Edition

Product typeBook
Published inJul 2021
Reading LevelIntermediate
PublisherPackt
ISBN-139781800564480
Edition2nd Edition
Languages
Python
Concepts
Data Science
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Author (1)
Stephen Klosterman
Stephen Klosterman
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Stephen Klosterman

Stephen Klosterman is a Machine Learning Data Scientist with a background in math, environmental science, and ecology. His education includes a Ph.D. in Biology from Harvard University, where he was an assistant teacher of the Data Science course. His professional experience includes work in the environmental, health care, and financial sectors. At work, he likes to research and develop machine learning solutions that create value, and that stakeholders understand. In his spare time, he enjoys running, biking, paddleboarding, and music.
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7. Test Set Analysis, Financial Insights, and Delivery to the Client

Activity 7.01: Deriving Financial Insights

Solution:

  1. Using the testing set, calculate the cost of all defaults if there were no counseling program.

    Use this code for the calculation:

    cost_of_defaults = np.sum(y_test_all * X_test_all[:,5])
cost_of_defaults

    The output should be this:

    60587763.0
  2. Calculate by what percent the cost of defaults can be decreased by the counseling program.

    The potential decrease in the cost of default is the greatest possible net savings of the counseling program, divided by the cost of all defaults in the absence of a program:

    net_savings[max_savings_ix]/cost_of_defaults

    The output should be this:

    0.2214260658542551

    Results indicate that we can decrease the cost of defaults by 22% using a counseling program, guided by predictive modeling.

  3. Calculate the net savings per account (considering all accounts it might be possible to counsel, in other words relative to the whole...
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Data Science Projects with Python - Second Edition
Published in: Jul 2021Publisher: PacktISBN-13: 9781800564480
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Author (1)

author image
Stephen Klosterman

Stephen Klosterman is a Machine Learning Data Scientist with a background in math, environmental science, and ecology. His education includes a Ph.D. in Biology from Harvard University, where he was an assistant teacher of the Data Science course. His professional experience includes work in the environmental, health care, and financial sectors. At work, he likes to research and develop machine learning solutions that create value, and that stakeholders understand. In his spare time, he enjoys running, biking, paddleboarding, and music.
Read more about Stephen Klosterman

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