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Exam IIBA-CBDA topic 1 question 23 discussion

Actual exam question from IIBA's IIBA-CBDA
Question #: 23
Topic #: 1
[All IIBA-CBDA Questions]

A professional association is funded by membership fees. The membership renewal occurs every 5 years. Although, they have a strong subscription rate each year, their renewal rate is low. They are working with an external firm specializing in Business Analytics to identify the groups of customers that have a high likelihood of cancelling their subscription after their first 5-year term ends.
This type of study is called:

  • A. Supervised learning
  • B. Untrained learning
  • C. Trained learning
  • D. Unsupervised learning
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Suggested Answer: A 🗳️
by Rabbitsfoot at July 18, 2024, 7:43 p.m.

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Rabbitsfoot
1 month, 3 weeks ago
Selected Answer: A
Supervised learning not in the guide.... none of the answers are. Research got me to this: 1.3 Bss Data Analytics Objectives: • Predictive: Analyzes past trends in data to provide future insights. Predictive analytics is used to answer the question “What is likely to happen?” • Example: Predicting profit or loss that is likely to happen in the next financial year. Supervised learning is the correct term for this type of study. It involves using historical data where the outcomes are known (in this case, whether customers canceled or renewed their subscriptions) to train a model. The model can then be used to predict the likelihood of cancellation for current customers based on their characteristics and behaviors. Supervised learning = Predictive analytics
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Rabbitsfoot
4 weeks ago
Correction - Supervised learning and predictive learning are closely related but not exactly the same. - Supervised learning is a type of machine learning where the model is trained on a labeled dataset. This means that the training data includes both the input features and the correct output (the label). The model learns to map inputs to the correct outputs, and it can be used for a variety of tasks, including both classification and regression. - Predictive learning refers to the process of using a model to predict outcomes based on input data. Predictive learning often relies on supervised learning, as the model is trained on historical data with known outcomes (labels) to make predictions about future or unseen data.
upvoted 1 times
Rabbitsfoot
4 weeks ago
In summary, predictive learning typically involves supervised learning, especially when the predictions are based on labeled historical data. However, predictive learning is a broader concept that encompasses the use of any technique to make predictions, which can include other methods beyond just supervised learning.
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