Question

which of the following is not a attribute of unsupervised learning​

Answer 1

Answer:

The above three written attributes are those which strongly support and are properties of a unsupervised learning. But in unsupervised learning it does not takes data and rules and never uses them as an input to develop a algorithm.

Answer 2

Which of the following is NOT an attribute of Unsupervised Learning?

The algorithm ingests unlabeled data, draws inferences, and finds patterns from unstructured data.

It is useful for clustering data, where data is grouped according to how similar it is to its neighbors and dissimilar to everything else.

It is useful for finding hidden patterns and or groupings in data and can be used to differentiate normal behavior with outliers such as fraudulent activity.

Takes data and rules as input and uses these inputs to develop an algorithm that will give us an answer.

The correct answer :

Takes data and rules as input and uses these inputs to develop an algorithm that will give us an answer

Explanation :

Unsupervised Learning is not characterized by that it takes data and rules as inputs and uses these inputs to develop an algorithm, which will give us an answer. The other three are qualities of unsupervised learning. The unsupervised learning algorithm captures unleveled data, extracts them, and then finds patterns from the protected data. It is also useful for clustering unusable learning data. It groups data according to what is similar to its neighbors and different from everything else. It is also very useful for spotting hidden patterns and clusters in unsupervised learning data. It can also be done to isolate normal dealings with outsiders such as fraudulent activity.

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