Machine Learning MCQs with answers Page - 4

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📊 Machine Learning
Q. What would you do in PCA to get the same projection as SVD?
  • (A) transform data to zero mean
  • (B) transform data to zero median
  • (C) not possible
  • (D) none of these
💬 Discuss
✅ Correct Answer: (A) transform data to zero mean
📊 Machine Learning
Q. The . . . . . . . . of the hyperplane depends upon the number of features.
  • (A) dimension
  • (B) classification
  • (C) reduction
  • (D) none of the above
💬 Discuss
✅ Correct Answer: (A) dimension
📊 Machine Learning
Q. What is the approach of basic algorithm for decision tree induction?
  • (A) greedy
  • (B) top down
  • (C) procedural
  • (D) step by step
💬 Discuss
✅ Correct Answer: (A) greedy
📊 Machine Learning
Q. Can we extract knowledge without apply feature selection
  • (A) Yes
  • (B) 0.06
  • (C) ---
  • (D) ---
💬 Discuss
✅ Correct Answer: (A) Yes
📊 Machine Learning
Q. 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
  • (A) 0.05
  • (B) validation data
  • (C) 0.07
  • (D) 0.09
💬 Discuss
✅ Correct Answer: (B) validation data
📊 Machine Learning
Q. When the number of classes is large Gini index is not a good choice.
  • (A) TRUE
  • (B) logistic regression
  • (C) ---
  • (D) ---
💬 Discuss
✅ Correct Answer: (A) TRUE
📊 Machine Learning
Q. Data used to build a data mining model.
  • (A) training data
  • (B) to transform the problem from regression to classification
  • (C) test data
  • (D) hidden data
💬 Discuss
✅ Correct Answer: (A) training data
📊 Machine Learning
Q. This technique associates a conditional probability value with each data instance.
  • (A) linear regression
  • (B) false - perceptrons are mathematically incapable of solving linearly inseparable functions, no matter what you do
  • (C) simple regression
  • (D) multiple linear regression
💬 Discuss
✅ Correct Answer: (B) false - perceptrons are mathematically incapable of solving linearly inseparable functions, no matter what you do
📊 Machine Learning
Q. Computers are best at learning
  • (A) facts.
  • (B) concepts.
  • (C) procedures.
  • (D) principles.
💬 Discuss
✅ Correct Answer: (A) facts.
📊 Machine Learning
Q. what is Feature scaling done before applying K-Mean algorithm?
  • (A) in distance calculation it will give the same weights for all features
  • (B) you always get the same clusters. if you use or dont use feature scaling
  • (C) in manhattan distance it is an important step but in euclidian it is not
  • (D) none of these
💬 Discuss
✅ Correct Answer: (A) in distance calculation it will give the same weights for all features

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