Answer / Awanish Kumar

Both model accuracy and model performance are important, but they serve different purposes. Model accuracy refers to how well a model performs on the training data (i.e., low error rate). Model performance, on the other hand, assesses the generalization ability of the model to unseen data (i.e., high accuracy on both training and test sets).

What according to you, is the standard approach to supervised learning?

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In what areas Pattern Recognition is used?

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Which one would you prefer to choose – model accuracy or model performance?

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Explain me what is machine learning?

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What is kernel SVM?

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You are given a dataset where the number of variables (p) is greater than the number of observations (n) (p>n). Which is the best technique to use and why ?

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What is PAC Learning?

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Tell me how a roc curve works?

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Explain the Algorithm Technique of Unsupervised Learning in Machine Learning?

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What is the difference between supervised and unsupervised machine learning?

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Can r be used for machine learning?

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What is bias-variance decomposition of classification error in ensemble method?

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