DATABASE FUNDAMENTALS
DATA WAREHOUSING AND DATA MINING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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supervised learning
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unsupervised learning
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reinforcement learning
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semi supervised learning
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Detailed explanation-1: -Answer-A) The task of inferring a model from labeled training data is called Supervised Learning.
Detailed explanation-2: -Supervised learning uses labeled datasets, whereas unsupervised learning uses unlabeled datasets. By “labeled” we mean that the data is already tagged with the right answer. A classification problem uses algorithms to classify data into particular segments.
Detailed explanation-3: -Supervised learning uses a training set to teach models to yield the desired output. This training dataset includes inputs and correct outputs, which allow the model to learn over time. The algorithm measures its accuracy through the loss function, adjusting until the error has been sufficiently minimized.
Detailed explanation-4: -In supervised learning, you create a function (or model) by using labeled training data that consists of input data and a wanted output. The supervision comes in the form of the wanted output, which in turn lets you adjust the function based on the actual output it produces.
Detailed explanation-5: -Explanation: supervised learning is a type of machine learning algorithm that is specifically designed to infer a model from labeled data.