A nearest neighbor approach is best used

Related MCQs

• Which among the following statements best describes our approach to learning decision trees
• Suppose, you have 2000 different models with their predictions and want to ensemble predictions of best x models. Now, which of the following can be a possible method to select the best x models for an ensemble?
• Which of the following is true about weighted majority votes? 1. We want to give higher weights to better performing models 2. Inferior models can overrule the best model if collective weighted votes for inferior models is higher than best model 3. Voting is special case of weighted voting
• There are also many univariate methods that can be used in order to select the best features according to specific criteria based on              .
• There are also many univariate methods that can be used in order to select the best features according to specific criteria based on________.
• his clustering approach initially assumes that each data instance represents a single cluster.
• What is the approach of basic algorithm for decision tree induction?
• What does K refers in the K-Means algorithm which is a non-hierarchical clustering approach?
• 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
• Which one of the following is not a major strength of the neural network approach?