Machine Learning MCQ Questions with answers and solutions Page 9

Q. 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 round shapes
4. Data points with non-convex shapes

(A) 1 and 2
(B) knowledge developer r
(C) 2 and 4
(D) 1, 2 and 4

💬 Discuss

✅ Correct Answer: (D) 1, 2 and 4

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. A person trained to interact with a human expert in order to capture their knowledge.

(A) knowledge programmer
(B) dataset
(C) knowledge engineer
(D) knowledge extractor

💬 Discuss

✅ Correct Answer: (D) knowledge extractor

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. In many classification problems, the target . . . . . . . . is made up of categorical labels which cannot immediately be processed by any algorithm.

(A) random_state
(B) kernel based principal component analysis
(C) test_size
(D) All above

💬 Discuss

✅ Correct Answer: (B) kernel based principal component analysis

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. What is PCA, KPCA and ICA used for?

(A) principal components analysis
(B) 2 and 3
(C) independent component analysis
(D) all above

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✅ Correct Answer: (D) all above

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. 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]

(A) 0.75
(B) 0.97
(C) 0.95
(D) 0.85

💬 Discuss

✅ Correct Answer: (B) 0.97

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. Suppose you are using RBF kernel in SVM with high Gamma value. What does this signify?

(A) The model would consider even far away points from hyperplane for modeling
(B) The model would consider only the points close to the hyperplane for modeling
(C) The model would not be affected by distance of points from hyperplane for modeling
(D) None of the above

💬 Discuss

✅ Correct Answer: (B) The model would consider only the points close to the hyperplane for modeling

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. The difference between the actual Y value and the predicted Y value found using a regression equation is called the

(A) slope
(B) residual
(C) outlier
(D) scatter plot

💬 Discuss

✅ Correct Answer: (A) slope

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. Which of the following method is used for multiclass classification?

(A) one vs rest
(B) loocv
(C) all vs one
(D) one vs another

💬 Discuss

✅ Correct Answer: (A) one vs rest

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. To determine association rules from frequent item sets

(A) only minimum confidence needed
(B) neither support not confidence needed
(C) both minimum support and confidence are needed
(D) minimum support is needed

💬 Discuss

✅ Correct Answer: (C) both minimum support and confidence are needed

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Q. The objective of the support vector machine algorithm is to find a hyperplane in an N-dimensional space(N the number of features) that distinctly classifies the data points.

(A) TRUE
(B) collinerity
(C) ---
(D) ---

💬 Discuss

✅ Correct Answer: (A) TRUE

Published by Mr. Dubey ⭐ 111.54K Points at 26-Apr-2024 12:21 pm in Machine Learning

Machine Learning MCQs with answers Page - 9

Q. 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 round shapes
4. Data points with non-convex shapes

Q. A person trained to interact with a human expert in order to capture their knowledge.

Q. In many classification problems, the target . . . . . . . . is made up of categorical labels which cannot immediately be processed by any algorithm.

Q. What is PCA, KPCA and ICA used for?

Q. 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]

Q. Suppose you are using RBF kernel in SVM with high Gamma value. What does this signify?

Q. The difference between the actual Y value and the predicted Y value found using a regression equation is called the

Q. Which of the following method is used for multiclass classification?

Q. To determine association rules from frequent item sets

Q. The objective of the support vector machine algorithm is to find a hyperplane in an N-dimensional space(N the number of features) that distinctly classifies the data points.

Programming Categories

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Machine Learning MCQs with answers Page - 9

Q. 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 round shapes 4. Data points with non-convex shapes

Q. A person trained to interact with a human expert in order to capture their knowledge.

Q. In many classification problems, the target . . . . . . . . is made up of categorical labels which cannot immediately be processed by any algorithm.

Q. What is PCA, KPCA and ICA used for?

Q. 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]

Q. Suppose you are using RBF kernel in SVM with high Gamma value. What does this signify?

Q. The difference between the actual Y value and the predicted Y value found using a regression equation is called the

Q. Which of the following method is used for multiclass classification?

Q. To determine association rules from frequent item sets

Q. The objective of the support vector machine algorithm is to find a hyperplane in an N-dimensional space(N the number of features) that distinctly classifies the data points.

Programming Categories

📱 Download Our App

Q. 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 round shapes
4. Data points with non-convex shapes