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Exercise 4: We have a dataset D using which we would like to train and evaluate a classifier. Suppose ⚫ we divide D into a training set denoted Dtrain and a test set denoted Dtest apply normalization on Dtrain using parameters estimated from Dtrain to create Dorm, which denotes the normalized training set. 'train Which of the following sequence of actions is a legitimate machine learning practice? A) ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dtest B) train ⚫ apply normalization on Dtest using parameters estimated from Dtest to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dorm train test ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dorm train test D) ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dtrain and assess its performance on Dorm 'test

Exercise 4: We have a dataset D using which we would like to train and evaluate a classifier. Suppose ⚫ we divide D into a training set denoted Dtrain and a test set denoted Dtest apply normalization on Dtrain using parameters estimated from Dtrain to create Dorm, which denotes the normalized training set. 'train Which of the following sequence of actions is a legitimate machine learning practice? A) ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dtest B) train ⚫ apply normalization on Dtest using parameters estimated from Dtest to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dorm train test ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dorm train test D) ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dtrain and assess its performance on Dorm 'test

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Exercise 4: We have a dataset D using which we would like to train and evaluate a classifier. Suppose ⚫ we divide D into a training set denoted Dtrain and a test set denoted Dtest ⚫ apply normalization on Dtrain using parameters estimated from Dtrain to create Dorm, which denotes the normalized training set. train' Which of the following sequence of actions is a legitimate machine learning practice? A) ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dtest B) train ⚫ apply normalization on Dtest using parameters estimated from Dtest to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dnorm C) test ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dorm train test D) ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dtrain and assess its performance on Dorm test
Transcribed Image Text:Exercise 4: We have a dataset D using which we would like to train and evaluate a classifier. Suppose ⚫ we divide D into a training set denoted Dtrain and a test set denoted Dtest ⚫ apply normalization on Dtrain using parameters estimated from Dtrain to create Dorm, which denotes the normalized training set. train' Which of the following sequence of actions is a legitimate machine learning practice? A) ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dtest B) train ⚫ apply normalization on Dtest using parameters estimated from Dtest to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dnorm C) test ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dorm and assess its performance on Dorm train test D) ⚫ apply normalization on Dtest using parameters estimated from Dtrain to create the normalized test set denoted Dorm test ⚫ train the classifier on Dtrain and assess its performance on Dorm test
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