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On what basis do you choose a classifier?
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Answer / Saumitra Kumar Mishra
Choosing a classifier in Machine Learning (ML) depends on various factors such as the type of data, the complexity of the problem, and the desired performance. For instance, if dealing with text data, Naive Bayes or Support Vector Machines (SVM) might be suitable choices. If dealing with image data, Convolutional Neural Networks (CNN) might be more appropriate. One can also compare classifiers based on their accuracy, precision, recall, F1 score, and area under the ROC curve.
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