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NEW QUESTION # 71
Supervised learning is a type of machine learning where the algorithm learns from a ______.
Answer: C
Explanation:
The correct answer is A. labeled dataset . Supervised learning is a machine learning method in which an algorithm is trained using data that already contains the correct output labels or target values. Each training example includes input features and a known answer, allowing the model to learn the relationship between the inputs and the expected output. Once trained, the model can use that learned relationship to classify or predict outcomes for new data.
An unlabeled dataset is used in unsupervised learning, where the model identifies hidden patterns, clusters, or relationships without predefined labels. An "explained dataset" is not a standard machine learning category.
Option D is incorrect because supervised learning does not learn from both labeled and unlabeled datasets as its primary definition. Option E is also incorrect because "explained dataset" is not the correct term.
Therefore, supervised learning learns from a labeled dataset , making A the correct answer.
NEW QUESTION # 72
Choose the CORRECT benefits a business can get through segmentation.
Answer: C
Explanation:
The correct answer is E. a, b and c only because all three statements describe valid business benefits of segmentation. Segmentation means dividing customers, markets, products, or users into meaningful groups based on shared characteristics, behaviors, needs, value, preferences, or risk profiles. In AI and analytics, segmentation helps organizations understand different customer groups more clearly and make better business decisions.
Statement A is correct because segmentation allows businesses to create targeted marketing communication.
Instead of sending the same message to everyone, companies can design messages that match each segment's interests, needs, and buying behavior. Statement B is also correct because segmentation can support pricing strategies by helping businesses offer the right pricing, discounts, bundles, or value propositions to the right customer groups. Statement C is correct because segmentation improves client service by helping teams understand customer expectations and deliver more relevant support, recommendations, and experiences.
Therefore, all listed benefits are correct, making E the best answer.
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NEW QUESTION # 73
Which of the following is a step for the Value Engineering Framework?
Answer: B
NEW QUESTION # 74
Which of the following is NOT CORRECT for the Elbow method?
Answer: C
Explanation:
The correct answer is E. None of the above because all three statements about the Elbow method are correct.
The Elbow method is commonly used in unsupervised learning, especially with K-means clustering, to help estimate an appropriate number of clusters. It works by running clustering with different values of K and measuring the within-cluster variation or distortion. As K increases, the error usually decreases, but after a certain point the improvement becomes much smaller. That point is visually interpreted as the "elbow." Statement A is correct because the Elbow method helps determine how many clusters should be formed.
Statement B is also correct because it is widely used with K-means clustering to select a suitable value of K.
Statement C is correct because the method is a heuristic, meaning it is a practical estimation technique rather than an exact mathematical guarantee. Since A, B, and C are all correct, none of them is NOT correct.
Therefore, the correct answer is E. None of the above .
NEW QUESTION # 75
Choose the CORRECT example of Supervised Learning.
Answer: D
Explanation:
The correct answer is B. House price prediction . Supervised learning is a machine learning approach where a model is trained using labeled data. In a house price prediction problem, the training data usually contains property features such as size, location, number of rooms, age of the house, and past selling prices. The known selling price acts as the label or target value. The model learns the relationship between the input features and the price, then predicts prices for new houses.
A driverless car is not the best single example because autonomous driving uses a combination of AI techniques, including supervised learning, reinforcement learning, computer vision, sensor fusion, planning, and control systems. ChatGPT is a generative AI language model and is not typically used as the basic example of supervised learning in this context. Since house price prediction directly represents supervised learning with labeled input-output data, the correct answer is B .
NEW QUESTION # 76
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