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Questions
1. Ensemble classifiers have been quite successful in generating supervised learning systems which exhibit very high accuracies. Can you justify this assertion using a specific example?
2. If the training examples are linearly separable, how many decision boundaries can separate positive from negative data points, using SVM? Which decision boundary does the SVM algorithm calculate?
3. Assume that there are three correlated classification models (A, B and C), such that the models A, B and C have prediction accuracy of 75%, 80% and 65%, respectively. What is the best possible way(s) of combining these models to optimize prediction accuracy? Justify your answer.
401173 - Introduction to Clinical Epidemiology - Western Sydney University - Write a focused research question for this particular problem that will help
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Collective Responsibility of Ministers Individual Ministerial Responsibility
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