In multiclass classification number of classes must be

Related MCQs

• Which of the following method is used for multiclass classification?
• Tree/Rule based classification algorithms generate ... rule to perform the classification.
• To control the size of the tree, we need to control the number of regions. One approach to do this would be to split tree nodes only if the resultant decrease in the sum of squares error exceeds some threshold. For the described method, which among the following are true? (a) It would, in general, help restrict the size of the trees (b) It has the potential to affect the performance of the resultant regression/classification model (c) It is computationally infeasible
• When the number of classes is large Gini index is not a good choice.
• The selling price of a house depends on many factors. For example, it depends on the number of bedrooms, number of kitchen, number of bathrooms, the year the house was built, and the square footage of the lot. Given these factors, predicting the selling price of the house is an example of ____________ task.
• Like the probabilistic view, the ________ view allows us to associate a probability of membership with each classification.
• Imagine, you are solving a classification problems with highly imbalanced class. The majority class is observed 99% of times in the training data. Your model has 99% accuracy after taking the predictions on test data. Which of the following is true in such a case? 1. Accuracy metric is not a good idea for imbalanced class problems. 2.Accuracy metric is a good idea for imbalanced class problems. 3.Precision and recall metrics are good for imbalanced class problems. 4.Precision and recall metrics aren’t good for imbalanced class problems.
• What is the precision value for following confusion matrix of binary classification?
• In SVM, RBF kernel with appropriate parameters to perform binary classification where the data is non-linearly seperable. In this scenario
• What is the Accuracy in percentage based on following confusion matrix of three class classification. Confusion Matrix C= [14 0 0] [ 1 15 0] [ 0 0 6]