COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Identifying birds in an image
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Grouping people into smaller groups based on buying habits
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Reducing the number of features in a data set
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Identifying anomalies in your data to label credit card transactions as fraudulent
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Detailed explanation-1: -Regression models Algorithms commonly used in supervised learning programs include the following: linear regression. logistic regression. neural networks.
Detailed explanation-2: -Regression is used to understand the relationship between dependable and independent variables. Moreover, it is a type of supervised learning that learns from labelled data sets to predict continuous output for different data in an algorithm.
Detailed explanation-3: -Which of the following best describes supervised learning? The training data contain missing labels or incomplete data. The training data match inputs to nodes in the network.
Detailed explanation-4: -One practical example of supervised learning problems is predicting house prices. How is this achieved? First, we need data about the houses: square footage, number of rooms, features, whether a house has a garden or not, and so on. We then need to know the prices of these houses, i.e. the corresponding labels.