Which one of the following is the main reason for pruning a Decision Tree?

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Question:
Which one of the following is the main reason for pruning a Decision Tree?

1.to save computing time during testing

2.to save space for storing the decision tree

3.to make the training set error smaller

4.to avoid overfitting the training set

Posted Date:-2022-06-22 06:36:46

More MCQS Questions and answers

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  3. In which neural net architecture, does weight sharing occur?
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  6. Which of the following is an application of NN (Neural Network)?
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  8. Which one of the following is not a major strength of the neural network approach?
  9. Which Statement is not true statement.
  10. 8 observations are clustered into 3 clusters using K-Means clustering algorithm. After first iteration clusters, C1, C2, C3 has following observations: C1: {(2,2), (4,4), (6,6)} C2: {(0,4), (4,0),(2,5)} C3: {(5,5), (9,9)} What will be the cluster centroids if you want to proceed for second iteration?
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  21. How the entries in the full joint probability distribution can be calculated?
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  23. In which of the following cases will K-Means clustering fail to give good results?
  24. In which of the following cases will K-means clustering fail to give good results? 1) Data points with outliers 2) Data points with different densities 3) Data points with nonconvex shapes
  25. Neural Networks are complex ______________ with many parameters.
  26. Suppose there are 25 base classifiers. Each classifier has error rates of e = 0.35. Suppose you are using averaging as ensemble technique. What will be the probabilities that ensemble of above 25 classifiers will make a wrong prediction? Note: All classifiers are independent of each other
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  30. The K-means algorithm:
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  38. what is Feature scaling done before applying K-Mean algorithm?
  39. What is gini index?
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