Evaluating Models Class 10 MCQ

Evaluating Models Class 10 MCQ – The CBSE has changed the syllabus of Std. X. The MCQs are made based on the new syllabus and based on the New CBSE textbook, Sample paper and Board Paper.  All the important Information are taken from the Artificial Intelligence Class X Textbook Based on CBSE Board Pattern.

Evaluating Models Class 10 MCQ

1. In a medical test for a rare disease, out of 1000 people tested, 50 actually have the disease while 950 do not. The test correctly identifies 40 out of the 50 people with the disease as positive, but it also wrongly identifies 30 of the healthy individuals as positive. What is the accuracy of the test?
a. 96%
b. 90%
c. 85%
d. 70%

2. A student solved 90 out of 100 questions correctly in a multiple-choice exam. What isthe error rate of the student’s answers?
a. 10%
b. 9%
c. 15%
d. 11%

3. In a spam email detection system, out of 1000 emails received, 300 are spam. The system correctly identifies 240 spam emails as spam, but it also marks 60 legitimate emails as spam. What is the precision of the system?
a. 80%
b. 70%
c. 75%
d. 90%

4. In a binary classification problem, a model predicts 70 instances as positive out of which 50 are actually positive. What is the recall of the model?
a. 50%
b. 70%
c. 80%
d. 100%

5. In a sentiment analysis task, a model correctly predicts 120 positive sentiments out of 200 positive instances. However, it also incorrectly predicts 40 negative sentiments as positive. What is the F1 score of the model?
a. 0.8
b. 0.67
c. 0.72
d. 0.82

6. A medical diagnostic test is designed to detect a certain disease. Out of 1000 people tested, 100 have the disease, and the test identifies 90 of them correctly. However, it also wrongly identifies 50 healthy people as having the disease. What is the precision of the test?
a. 90%
b. 80%
c. 70%
d. 64.3%

7. A teacher’s marks prediction system predicts the marks of a student as 75, but the actual marks obtained by the student are 80. What is the absolute error in the prediction?
a. 5
b. 10
c. 15
d. 20

8. The goal when evaluating an AI model is to:
a. Maximize error and minimize accuracy
b. Minimize error and maximize accuracy
c. Focus solely on the number of data points used
d. Prioritize the complexity of the model

9. A high F1 score generally suggests:
a. A significant imbalance between precision and recall
b. A good balance between precision and recall
c. A model that only performs well on specific data points
d. The need for more training data

10. How is the relationship between model performance and accuracy described?
a. Inversely proportional
b. Not related
c. Directly proportional
d. Randomly fluctuating

11. Assertion: Accuracy is an evaluation metric that allows you to measure the total number of predictions a model gets right.
Reasoning: The accuracy of the model and performance of the model is directly proportional, and hence better the performance of the model, the more accurate are the predictions.
Choose the correct option:
a. Both A and R are true and R is the correct explanation for A
b. Both A and R are true and R is not the correct explanation for A
c. A is True but R is False
d. A is false but R is True

12. Assertion: The sum of the values in a confusion matrix’s row represents the total number of instances for a given actual class.
Reasoning: This enables the calculation of class-specific metrics such as precision and recall, which are essential for evaluating a model’s performance across different classes.
Choose the correct option:
a. Both A and R are true and R is the correct explanation for A
b. Both A and R are true and R is not the correct explanation for A
c. A is True but R is False
d. A is false but R is True

13. The Indian Government banned a few apps stating – “servers in the hostile nation are receiving and using the acquired data improperly”. Which terminology suits best for this action?
a. AI Ethics
b. Data Privacy
c. AI Bias
d. AI Access

14. Which of the following is defined as the measure of balance between precision and recall ? (CBSE 2022 – 2023)
a. Accuracy
b. F1 Score
c. Reliability
d. Punctuality

15. Prediction and Reality can be easily mapped together with the help of :
a. Prediction
b. Reality
c. Accuracy
d. Confusion Matrix

16. F1 Score is the measure of the balance between
a. Accuracy and Precision
b. Precision and Recall
c. Recall and Accuracy
d. Recall and Reality

17. Statment1: The output given by the AI model is known as reality.
Statement2:The real scenario is known as Prediction.
a. Both Statement1 and Statement2 are correct
b. Both Statement1 and Statement2 are incorrect
c. Statement1 is correct but Statement2 is incorrect
d. Statement2 is correct but Statement1 is incorrect

18. Statement 1: Confusion matrix is an evaluation metric.
Statement 2 : Confusion Matrix is a record which helps in evaluation. (CBSE 2023 – 2024)
a. Both Statement 1 and Statement 2 are correct.
b. Both Statement 1 and Statement 2 are incorrect.
c. Statement 1 is correct and Statement 2 is incorrect.
d. Statement 2 is correct and Statement 1 is incorrect.

19. How many channels does a colour image have?

20. Which feature of NLP helps in understanding the emotions of the people mentioned with the feedback?
a. Virtual Assistants
b. Sentiment Analysis
c. Text classification
d. Automatic Summarization

21. Which of the following represent a machine that is smart but not considered Artificial Intelligence (AI) enabled? (CBSE 2023 – 2024)
a. A robotic vacuum cleaner that can navigate and clean floors autonomously.
b. A chatbot that engages in natural language conversations and answers questions.
c. A smartphone with facial recognition for unlocking the device.
d. A digital alarm clock that rings at a set time every morning.

22. Which evaluation parameter takes into consideration all the correct predictions?

23. Which of the following is incorrect?
i) Testing data is the one on which we train and fit our model basically to fit the parameters
ii) Training data is used only to assess performance of model
iii) Testing data is the unseen data for which predictions have to be made
a. i) and iii) only
b. i) and ii) only
c. ii) and iii) only
d. i), ii) and iii)

24. While evaluating a model’s performance, recall parameter considers (CBSE 2022 – 2023)
i) False positive
ii) True positive
iii) False negative
iv) True negative
Choose the correct option :
a. only i)
b. ii) and iii)
c. ii) and iv)
d. i) and iv)

25. Amazon had been working on a secret AI recruiting tool. The machine-learning specialists uncovered a big problem: their new recruiting engine did not like women. The system taught itself that male candidates were preferable. It penalized resumes that included the word “women”. This led to the failure of the tool. This is an example of
a. Data Privacy
b. AI access
c. AI Bias
d. Data Exploration

26. Which of the following represents an example of a recommendation system? (CBSE 2023 – 2024)
a. An online clothing store that offers a wide variety of clothing options.
b. A search engine that retrieves relevant web pages based on user queries.
c. An e-commerce website that displays customer reviews and ratings for products.
d. A music streaming platform that suggests songs and playlists based on user listening history.

27. Two conditions when prediction matches with the reality are true positive and __. (CBSE 2022 – 2023)

28. The term Sentence Segmentation is
a. the whole corpus is divided into sentences
b. to undergo several steps to normalise the text to a lower level
c. in which each sentence is then further divided into tokens
d. the process in which the affixes of words are removed

29. Which of the following statements is true for the term Evaluation?
a. Helps in classifying the type and genre of a document.
b. It helps in predicting the topic for a corpus.
c. Helps in understanding the reliability of any AI model
d. Process to extract the important information out of a corpus.

30. Which of the following talks about how true the predictions are by any model ? (CBSE 2022 – 2023)
a. Accuracy
b. Reliability
c. Recall
d. F1 score

31. What is the primary need for evaluating an AI model’s performance in the AI Model Development process? (CBSE 2023 – 2024)
a. To increase the complexity of the model.
b. To visualize the data.
c. To assess how well the chosen model will work in future.
d. To reduce the amount of data used for training.

32. ____________is defined as the percentage of correct predictions out of all the observations.
a. Predictions
b. Accuracy
c. Reality
d. F1 Score

33. Name any two search engines. (CBSE 2023 – 2024)

34. ___________ is the process of understanding the reliability of any AI model, based on outputs by feeding
test dataset into the model and comparing with actual answers.
a. Evaluation 
b. Problem Scoping
c. Data acquisition
d. Data Exploration

35. If model will simply remember the whole training set, and will therefore always predict the correct label for any point in the training set. This is known as ____________.
a. Overfitting 
b. Overriding
c. Over remembering
d. None of the above

36. The result of comparison between the prediction and reality can be recorded in what we call the __________.
a. Overfitting
b. Problem Scoping
c. Confusion Matrix 
d. Data acquisition

37. The _____________ allows us to understand the prediction results.
a. Overfitting
b. Problem Scoping
c. Confusion Matrix 
d. Data acquisition

38. _________ is defined as the percentage of correct predictions out of all the observations.
a. Overfitting
b. Accuracy
c. Confusion Matrix
d. Data acquisition

39. _______ is defined as the percentage of true positive cases versus all the cases where the prediction is true.
a. Overfitting
b. Accuracy
c. Precision 
d. Data acquisition

40. ___________ can be defined as the fraction of positive cases that are correctly identified.
a. Recall 
b. Accuracy
c. Precision
d. Data acquisition

41. ___________ can be defined as the measure of balance between precision and recall.
a. Recall
b. Accuracy
c. Precision
d. F1 Score 

42. Statement 1: Overfitting occurs when a model memorizes the training data rather than learning patterns.
Statement 2: Unsing the same data for training and evalution helps the model give accurate results. (Board Paper 2025-26)
a. Both statements are correct
b. Both statement are incorrect
c. Statement 1 is correct but statement 2 is incorrect
d. Statement 1 is incorrect but statement 2 is correct

43. In the context of autonomous vehicle safety system. Which type of error would be most critical to minimize? (Board Paper 2025-26)
a. False Positive (detecting danger when there ist any)
b. False Negative (Failing to detect actual danger)
c. True Positive (detecting danger correctly)
d. True Negative (correctly identifing that there is no danger)

44. In supervised learning. What is the purpose of the testing dataset? (Board Paper 2025-26)
a. To train the model.
b. To evalute the models accuracy
c. To create new features
d. To lable the data

45. In a fire alarm system. if the model predicts “Fire Present” when there is acutally no fire, this is classfied as __. (Board Paper 2025-26)
a. True Positieve (TP)
b. True Negative (TN)
c. False Positive (FP)
d. False Negative (FN)

46. Precision is defiend as _. (Board Paper 2025-26)
a. The ratio of correctly predicted positive observations to totlal observations.
b. The ration of correctly predicted positve observations to total predicted positve observations.
c. The ration of correctly predicted negative observations to total observations.
d. The harmonic mean of true positvies and true negatives.

47. State True or False:
In machine learning the error is used to see how accurately the model can predict data. (Board Paper 2025-26)

48. An AI model was tested with 1000 test samples. If True Postive (TP) = 200, True Negative (TN) = 600, False Positive (FP) = 100, Fase Negative (FN) = 100, how many total predictions wer correct? (Board Paper 2025-26)
a. 300
b. 600
c. 800
d. 900

49. Which condition of evaluation does the following diagram indicate ? (Board Paper 2024-25)
Prediction : No
Reality : Yes
a. False Positive
b. False Negative
c. True Positive
d. True Negative

50. Statement 1 : Overfitting is not recommended for evaluation of a model. (Board Paper 2024-25)
Statement 2 : This is because the model will simply remember the whole training set, and will therefore always predict the correct label for any point in the training set.
a. Both Statement 1 and Statement 2 are correct.
b. Both Statement 1 and Statement 2 are incorrect.
c. Statement 1 is correct but Statement 2 is incorrect.
d. Statement 2 is correct but Statement 1 is incorrect.

51. It is one of the parameters for evaluating a model’s performance and is defined as the percentage of true positive cases versus all the cases where the prediction is true. Which of the following evaluation parameter is this ? (Board Paper 2024-25)
a. Precision
b. Recall
c. F1 score
d. Accuracy

52. __ is defined as the percentage of correct predictions out of all the observations. (Comp Board Paper 2024-25)
a. Precision
b. Accuracy
c. Recall
d. F1

53. In a quality control system for manufacturing, which scenario represents a false negative? (Comp Board Paper 2024-25)
a. When a defective product is correctly identified as defective.
b. When a non-defective product is inaccurately identified as defective.
c. When a non-defective product is correctly identified as non-defective.
d. When a defective product is mistakenly identified as non-defective.

54. When a model is evaluated on the training data it always predicts correctly. This is known as __. (Comp Board Paper 2024-25)

55. Which of the following is not true about Confusion Matrix? (Comp Board Paper 2024-25)
a. It allows us to understand prediction results.
b. It is a Model Training Matrix.
c. It helps in evaluation of machine learning models.
d. It is used to record comparison between prediction and reality.

56. Name any two search engines. (Comp Board Paper 2024-25)

57. __ is one of the parameter for evaluating a model’s performance and is defined as the fraction of positive cases that are correctly identified. (Board Paper 2023-24)
a. Precision
b. Accuracy
c. Recall
d. F1

58. In spam email detection, which of the following will be considered as “False Negative”? (Board Paper 2023-24)
a. When a legitimate email is accurately identified as not spam.
b. When a spam email is mistakenly identified as legitimate.
c. When an email is accurately recognised as spam.
d. When an email is inaccurately labelled as important.

59. Statement 1: Confusion matrix is an evaluation metric. (Board Paper 2023-24)
Statement 2: Confusion Matrix is a record which helps in evaluation.
a. Both Statement 1 and Statement 2 are correct.
b. Both Statement 1 and Statement 2 are incorrect.
c. Statement 1 is correct and Statement 2 is incorrect.
d. Statement 2 is correct and Statement 1 is incorrect.

60. What is the primary need for evaluating an AI model’s performance in the AI Model Development process? (Board Paper 2023-24)
a. To increase the complexity of the model.
b. To visualize the data.
c. To assess how well the chosen model will work in future.
d. To reduce the amount of data used for training.

61. Statement 1: To evaluate a model’s performance, we need either precision or recall.
Statement 2: When the value of both Precision and Recall is 1, the F1 score is 0. (Board Paper 2023-24)
a. Both statement 1 and statement 2 are correct.
b. Both statement 1 and statement 2 are incorrect.
c. Statement 1 is correct, but statement 2 is incorrect.
d. Statement 1 is incorrect, but statement 2 is correct.

62. Which of the following is defined as the measure of balance between precision and recall? (Board Paper 2022-23)
a. Accuracy
b. F1 Score
c. Reliability
d. Punctuality

63. __ helps to find the best model that represents our data and how well the chosen model will work in future. (Board Paper 2022-23)

64. While evaluating a model’s performance, recall parameter considers: (Board Paper 2022-23)
(i) False positive
(ii) True positive
(iii) False negative
(iv) True negative
Choose the correct option:
a. only (i)
b. (ii) and (iii)
c. (iii) and (iv)
d. (i) and (iv)

65. Two conditions when prediction matches with the reality are true positive and __. (Board Paper 2022-23)

66. __ is a term used for any word or number or special character occurring in a sentence. (Token / Punctuator) (Board Paper 2022-23)

67. Which of the following talks about how true the predictions are by any model? (Board Paper 2022-23)
a. Accuracy
b. Reliability
c. Recall
d. F1 score

68. _ is an integral part of the model development process that helps to find the best model that represents our data and how well the chosen model will work in the future. (Sample Paper 2025-26)

69. In a spam email detection system, out of 1000 emails received, 300 are spam. The system correctly identifies 240 spam emails as spam, but it also marks 60 legitimate emails as spam. What is the precision of the system? (Sample Paper 2025-26)
a. 0.80
b. 0.70
c. 0.75
d. 0.90

70. Assertion a.: In machine learning, a model with lower error is considered to perform better on a given dataset.
Reason (R): Error helps us evaluate how accurately a model can predict both training and unseen data, which is why it is used to select the best performing model. (Sample Paper 2025-26)
a. Both A and R are correct, and R is the correct explanation of A
b. Both A and R are correct, but R is not the correct explanation of A
c. A is correct, but R is incorrect
d. A is incorrect, but R is correct

71. Statement 1: The testing data set is a collection of examples given to the model to analyze and learn.
Statement 2: The training data set is used to test the accuracy of the model.
Which of the following is correct? (Sample Paper 2025-26)
a. Both Statement 1 and Statement 2 are correct.
b. Both Statement 1 and Statement 2 are incorrect.
c. Only Statement 1 is correct.
d. Only Statement 2 is correct.

72. Why is it not recommended to evaluate a machine learning model using the same data on which it was trained? (Sample Paper 2025-26)
a. It helps the model learn faster
b. It reduces bias in the dataset
c. It improves the performance of the model on unseen data
d. It may lead to overfitting and give an overly optimistic accuracy

73. A house was predicted to cost ₹4,53,000, but the actual selling price was ₹4,88,000.
What is the error rate of this prediction (rounded to three decimal places)? (Sample Paper 2025-26)
a. 0.058
b. 0.071
c. 0.092
d. 0.117

74. _ is the outcome of the model wrongly predicting the negative class as positive class. (Sample Paper 2025-26)

75. F1 Score is the measure of the balance between (Sample Paper 2024-25)
a. Accuracy and Precision
b. Precision and Recall
c. Recall and Accuracy
d. Recall and Reality

76. Statment1: The output given by the AI model is known as reality.
Statement2:The real scenario is known as Prediction. (Sample Paper 2024-25)
a. Both Statement1 and Statement2 are correct
b. Both Statement1 and Statement2 are incorrect
c. Statement1 is correct but Statement2 is incorrect
d. Statement2 is correct but Statement1 is incorrect

77. Sarthak made a face mask detector system for which he had collected the dataset and used all the dataset to train the model. Then, he used the same data to evaluate the model which resulted in the correct answer all the time but was not able to perform with unknown dataset. Name the concept. (Sample Paper 2024-25)

78. Which evaluation parameter takes into consideration all the correct predictions? (Sample Paper 2024-25)

79. Which one of the following scenario result in a high false positive cost? (Sample Paper 2024-25)
a. viral outbreak
b. forest fire
c. flood
d. spam filter

80. The output given by the AI machine is known as __ (Prediction/ Reality) (Sample Paper 2022-23)

81. _ is used to record the result of comparison between the prediction and reality. It is not an evaluation metric but a record which can help in evaluation. (Sample Paper 2022-23)

82. Raunak was learning the conditions that make up the confusion matrix. He came across a scenario in which the machine that was supposed to predict an animal was always predicting not an animal. What is this condition called? (Sample Paper 2022-23)
a. False Positive
b. True Positive
c. False Negative
d. True Negative

83. Which two evaluation methods are used to calculate F1 Score? (Sample Paper 2022-23)
a. Precision and Accuracy
b. Precision and Recall
c. Accuracy and Recall
d. Precision, F1 score

84. Which of the following statements is not true about overfitting models? (Sample Paper 2022-23)
a. This model learns the pattern and noise in the data to such extent that it harms the performance of the model on the new dataset
b. Training result is very good and the test result is poor
c. It interprets noise as patterns in the data
d. The training accuracy and test accuracy both are low

85. Priya was confused with the terms used in the evaluation stage. Suggest her the term used for the percentage of correct predictions out of all the observations. (Sample Paper 2022-23)
a. Accuracy
b. Precision
c. Recall
d. F1 Score

86. Which of the following is incorrect? (Sample Paper 2021-22)
i) Testing data is the one on which we train and fit our model basically to fit the parameters
ii) Training data is used only to assess performance of model
iii) Testing data is the unseen data for which predictions have to be made
a. i) and iii) only
b. i) and ii) only
c. ii) and iii) only
d. i), ii) and iii)

87. Unscramble the letters and find the parameter that is NOT used in evaluation stage (Sample Paper 2021-22)
a. CMVETEEHAIN
b. ONSIPRICE
c. RYAUACCC
d. ECLARL

88. ____________is defined as the percentage of correct predictions out of all the observations. (Sample Paper 2020-21)
a. Predictions
b. Accuracy
c. Reality
d. F1 Score

89. What will be the outcome, if the Prediction is “Yes” and it matches with the Reality? What will be the outcome, if the Prediction is “Yes” and it does not match the Reality? (Sample Paper 2020-21)
a. True Positive, True Negative
b. True Negative, False Negative
c. True Negative, False Positive
d. True Positive, False Positive

90. Recall-Evaluation method is _. (Sample Paper 2020-21)
a. defined as the fraction of positive cases that are correctly identified.
b. defined as the percentage of true positive cases versus all the cases where the prediction is true.
c. defined as the percentage of correct predictions out of all the observations.
d. comparison between the prediction and reality

91. Differentiate between Prediction and Reality. (Sample Paper 2020-21)
a. Prediction is the input given to the machine to receive the expected result of the reality.
b. Prediction is the output given to match the reality.
c. The prediction is the output which is given by the machine and the reality is the real scenario in which the prediction has been made.
d. Prediction and reality both can be used interchangeably.

92. Which of the following statements is true for the term Evaluation? (Sample Paper 2020-21)
a. Helps in classifying the type and genre of a document.
b. It helps in predicting the topic for a corpus.
c. Helps in understanding the reliability of any AI model
d. Process to extract the important information out of a corpus.

93. Prediction and Reality can be easily mapped together with the help of : (Sample Paper 2020-21)
a. Prediction
b. Reality
c. Accuracy
d. Confusion Matrix

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