COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Data Training
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Training Data
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Transfer Data
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Test Data
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Detailed explanation-1: -Machine learning algorithms build a model based on sample data, known as “training data, ” in order to make predictions or decisions without being explicitly programmed to do so.
Detailed explanation-2: -In its application across business problems, machine learning is also referred to as predictive analytics.
Detailed explanation-3: -Training data is also known as training dataset, learning set, and training set. It’s an essential component of every machine learning model and helps them make accurate predictions or perform a desired task. Simply put, training data builds the machine learning model.
Detailed explanation-4: -Unsupervised learning, also known as unsupervised machine learning, uses machine learning algorithms to analyze and cluster unlabeled datasets. These algorithms discover hidden patterns or data groupings without the need for human intervention.
Detailed explanation-5: -Decision Tree Algorithms: These methods construct a tree-based model constructed on the decisions made by examining the values of the attributes. Decision trees are used for both classification and regression problems. Some of the well-known decision tree algorithms are: Classification and Regression Tree, C4.