MCQs > IT & Programming > Machine Learning MCQs > Basic Machine learning MCQs

Basic Machine learning MCQ

1. When is a decision tree most commonly used?

Answer

Correct Answer: For supervised machine learning binary classification challenges

Note: This Question is unanswered, help us to find answer for this one

2. Which project might be best suited for supervised machine learning?

Answer

Correct Answer: Predicting a risk score

Note: This Question is unanswered, help us to find answer for this one

3. What is the best definition for bias in your data model?

Answer

Correct Answer: Bias is the gap between your predicted value and the outcome.

Note: This Question is unanswered, help us to find answer for this one

4. What is ensemble modeling?

Answer

Correct Answer: When you use several ensembles of machine learning algorithms

Note: This Question is unanswered, help us to find answer for this one

5. K-means clustering is what type of machine learning algorithm?

Answer

Correct Answer: Unsupervised

Note: This Question is unanswered, help us to find answer for this one

6. What is conditional probability?

Answer

Correct Answer: The probability that doing one thing has an impact on another thing

Note: This Question is unanswered, help us to find answer for this one

7. In supervised machine learning, data scientist often have the challenge of balancing between underfitting or overfitting their data model. They often have to adjust the training set to make better predictions. What is this balance called?

Answer

Correct Answer: Bias-variance trade-off

Note: This Question is unanswered, help us to find answer for this one

8. You work for a startup that is trying to develop a software tool that will scan the internet for pictures of people using specific tools. The chief executive is very interested in using machine learning algorithms. What would you recommend as the best place to start?

Answer

Correct Answer: Use supervised machine learning to classify photographs based on a predetermined training set.

Note: This Question is unanswered, help us to find answer for this one

9. What is the difference between unstructured and structured data?

Answer

Correct Answer: Structured data has clearly defined data types.

Note: This Question is unanswered, help us to find answer for this one

10. What is one of the most effective way to correct for underfitting your model to the data?

Answer

Correct Answer: Add more predictors

Note: This Question is unanswered, help us to find answer for this one

11. In the 1983 movie WarGames, the computer learns how to master the game of chess by playing against itself. What machine learning method was the computer using?

Answer

Correct Answer: Reinforcement learning

Note: This Question is unanswered, help us to find answer for this one

12. The data in your model has low bias and low variance. How would you expect the data points to be grouped together on the diagram?

Answer

Correct Answer: They would be grouped tightly together in the predicted outcome.

Note: This Question is unanswered, help us to find answer for this one

13. What is lazy learning?

Answer

Correct Answer: When the learning happens continuously

Note: This Question is unanswered, help us to find answer for this one

14. In statistics, what is defined as the probability of a hypothesis test of finding an effect - if there is an effect to be found?

Answer

Correct Answer: Power

Note: This Question is unanswered, help us to find answer for this one

15. Which choice is the best example of labeled data?

Answer

Correct Answer: A spreadsheet

Note: This Question is unanswered, help us to find answer for this one

16. You need to select a machine learning process to run a distributed neural network on a mobile application. Which would you choose?

Answer

Correct Answer: Tensowflow Lite

Note: This Question is unanswered, help us to find answer for this one

17. You need to quickly label thousands of images to train a model. What should you do?

Answer

Correct Answer: Use naive Bayes to automatically generate labels.

Note: This Question is unanswered, help us to find answer for this one

18. Which loss function would fit best in a categorical (discrete) supervised learning ?

Answer

Correct Answer: Binary Crossentropy

Note: This Question is unanswered, help us to find answer for this one

19. What is the main motivation for using activation functions in ANN?

Answer

Correct Answer: Capturing complex non-linear patterns

Note: This Question is unanswered, help us to find answer for this one

20. Which of the following methods can use either as an unsupervised learning or as a dimensionality reduction technique?

Answer

Correct Answer: PCA

Note: This Question is unanswered, help us to find answer for this one

21. The new dataset you have just scraped seems to exhibit lots of missing values. What action will help you minimizing that problem?

Answer

Correct Answer: Imputation

Note: This Question is unanswered, help us to find answer for this one

22. (Mostly) whenever we see kernel visualizations online (or some other reference) we are actually seeing:

Answer

Correct Answer: What kernels extract

Note: This Question is unanswered, help us to find answer for this one

23. Asian user complains that your company's facial recognition model does not properly identify their facial expressions. What should you do?

Answer

Correct Answer: Include Asian faces in your training data and retrain your model.

Note: This Question is unanswered, help us to find answer for this one

24. What does it mean to underfit your data model?

Answer

Correct Answer: There is not a lot of variance but there is a high bias.

Note: This Question is unanswered, help us to find answer for this one

25. ___ refers to a model that can neither model the training data nor generalize to new data.

Answer

Correct Answer: Underfitting

Note: This Question is unanswered, help us to find answer for this one

26. Compared to the variance of the Maximum Likelihood Estimate (MLE), the variance of the Maximum A Posteriori (MAP) estimate is ___

Answer

Correct Answer: Lower

Note: This Question is unanswered, help us to find answer for this one

27. The error function most suited for gradient descent using logistic regression is

Answer

Correct Answer: The cross-entropy function.

Note: This Question is unanswered, help us to find answer for this one

28. Suppose we would like to perform clustering on spatial data such as the geometrical locations of houses. We wish to produce clusters of many different sizes and shapes. Which of the following methods is the most appropriate?

Answer

Correct Answer: Density-based clustering

Note: This Question is unanswered, help us to find answer for this one

29. Which of the following is NOT supervised learning?

Answer

Correct Answer: PCA

Note: This Question is unanswered, help us to find answer for this one

30. The model will be trained with data in one single batch is known as ?

Answer

Correct Answer: Both A and B

Note: This Question is unanswered, help us to find answer for this one

31. Your data science team is working on a machine learning product that can act as an artificial opponent in video games. The team is using a machine learning algorithm that focuses on rewards: If the machine does some things well, then it improves the quality of the outcome. How would you describe this type of machine learning algorithm?

Answer

Correct Answer: Reinforcement learning

Note: This Question is unanswered, help us to find answer for this one

32. You and your data science team have 1 TB of example data. What do you typically do with that data?

Answer

Correct Answer: You label it big data.

Note: This Question is unanswered, help us to find answer for this one

33. You work for a website that enables customers see all images of themselves on the internet by uploading one self-photo. Your data model uses 5 characteristics to match people to their foto: color, eye, gender, eyeglasses and facial hair. Your customers have been complaining that get tens of thousands of photos without them. What is the problem?

Answer

Correct Answer: You are underfitting the model to the data

Note: This Question is unanswered, help us to find answer for this one

34. Your data science team wants to use machine learning to better filter out spam messages. The team has gathered a database of 100,000 messages that have been identified as spam or not spam. If you are using supervised machine learning, what would you call this data set?

Answer

Correct Answer: Training set

Note: This Question is unanswered, help us to find answer for this one

35. Someone of your data science team recommends that you use decision trees, naive Bayes and K-nearest neighbor, all at the same time, on the same training data, and then average the results. What is this an example of?

Answer

Correct Answer: Ensemble modeling

Note: This Question is unanswered, help us to find answer for this one

36. Many of the advances in machine learning have come from improved ___.

Answer

Correct Answer: Algorithms

Note: This Question is unanswered, help us to find answer for this one

37. You work for a hospital that is tracking the community spread of a virus. The hospital created a smartwatch application that uploads body temperature data from hundreds of thousands of participants. What is the best technique to analyze the data?

Answer

Correct Answer: Use Supervised machine learning to classify people by body temperature.

Note: This Question is unanswered, help us to find answer for this one

38. The security company you work for is thinking about adding machine learning algorithms to their computer network threat detection appliance. What is one advantage of using machine learning?

Answer

Correct Answer: It could better protect against undiscovered threats.

Note: This Question is unanswered, help us to find answer for this one

39. In 2015, Google created a machine learning system that could beat a human in the game of Go. This extremely complex game is thought to have more gameplay possibilities than there are atoms of the universe. The first version of the system won by observing hundreds of thousands of hours of human gameplay; the second version learned how to play by getting rewards while playing against itself. How would you describe this transition to different machine learning approaches?

Answer

Correct Answer: The system went from supervised learning to reinforcement learning.

Note: This Question is unanswered, help us to find answer for this one

40. You work for a large pharmaceutical company whose data science team wants to use unsupervised learning machine algorithms to help discover new drugs. What is an advantage to this approach?

Answer

Correct Answer: The algorithms will cluster together drugs that have similar traits.

Note: This Question is unanswered, help us to find answer for this one

41. In the HBO show Silicon Valley, one of the characters creates a mobile application called Not Hot Dog. It works by having the user take a photograph of food with their mobile device. Then the app says whether the food is a hot dog. To create the app, the software developer uploaded hundreds of thousands of pictures of hot dogs. How would you describe this type of machine learning?

Answer

Correct Answer: Supervised machine learning

Note: This Question is unanswered, help us to find answer for this one

42. In K-nearest neighbor, the closer you are to neighbor, the more likely you are to

Answer

Correct Answer: Share common characteristics

Note: This Question is unanswered, help us to find answer for this one

43. Why is it important for machine learning algorithms to have access to high-quality data?

Answer

Correct Answer: If the data is low quality, you will get inaccurate results.

Note: This Question is unanswered, help us to find answer for this one

44. With traditional programming, the programmer typically inputs commands. With machine learning, the programmer inputs

Answer

Correct Answer: Data

Note: This Question is unanswered, help us to find answer for this one

45. Which choice is best for binary classification?

Answer

Correct Answer: Logistic regression

Note: This Question is unanswered, help us to find answer for this one

46. Are data model bias and variance a challenge with unsupervised learning?

Answer

Correct Answer: Yes, data model bias is a challenge when the machine creates clusters.

Note: This Question is unanswered, help us to find answer for this one

47. You are using K-nearest neighbor and you have a K of 1. What are you likely to see when you train the model?

Answer

Correct Answer: High variance and low bias

Note: This Question is unanswered, help us to find answer for this one

48. You work for a large credit card processing company that wants to create targeted promotions for its customers. The data science team created a machine learning system that groups together customers who made similar purchases, and divides those customers based on customer loyalty. How would you describe this machine learning approach?

Answer

Correct Answer: It uses unsupervised learning to cluster together transactions and unsupervised learning to classify the customers.

Note: This Question is unanswered, help us to find answer for this one

49. Your machine learning system is attempting to describe a hidden structure from unlabeled data. How would you describe this machine learning method?

Answer

Correct Answer: Unsupervised learning

Note: This Question is unanswered, help us to find answer for this one

50. Your data science team wants to use the K-nearest neighbor classification algorithm. Someone on your team wants to use a K of 25. What are the challenges of this approach?

Answer

Correct Answer: Higher K values lower the variance but increase the bias.

Note: This Question is unanswered, help us to find answer for this one

51. Your data science team must build a binary classifier, and the number one criterion is the fastest possible scoring at deployment. It may even be deployed in real time. Which technique will produce a model that will likely be fastest for the deployment team use to new cases?

Answer

Correct Answer: Logistic regression

Note: This Question is unanswered, help us to find answer for this one

52. You created machine learning system that interacts with its environment and responds to errors and rewards. What type of machine learning system is it?

Answer

Correct Answer: Reinforcement learning

Note: This Question is unanswered, help us to find answer for this one

53. Which statement about K-means clustering is true?

Answer

Correct Answer: In K-means clustering, the initial centroids are sometimes randomly selected.

Note: This Question is unanswered, help us to find answer for this one

54. Self-organizing maps are specialized neural network for which type of machine learning?

Answer

Correct Answer: Semi-supervised learning

Note: This Question is unanswered, help us to find answer for this one

55. Random forest is modified and improved version of which earlier technique?

Answer

Correct Answer: Bagged trees

Note: This Question is unanswered, help us to find answer for this one

56. Your organization allows people to create online professional profiles. A key feature is the ability to create clusters of people who are professionally connected to one another. What type of machine learning method is used to create these clusters?

Answer

Correct Answer: Unsupervised machine learning

Note: This Question is unanswered, help us to find answer for this one

57. Your company wants you to build an internal email text prediction model to speed up the time that employees spend writing emails. What should you do?

Answer

Correct Answer: Include training email data from all employees.

Note: This Question is unanswered, help us to find answer for this one

58. You are working on a project that involves clustering together images of different dogs. You take image and identify it as your centroid image. What type machine learning algorithm are you using?

Answer

Correct Answer: K-means clustering

Note: This Question is unanswered, help us to find answer for this one

59. What is stacking?

Answer

Correct Answer: The predictions of one model become the inputs another.

Note: This Question is unanswered, help us to find answer for this one

60. What is one reason not to use the same data for both your training set and your testing set?

Answer

Correct Answer: You will almost certainly overfit the model.

Note: This Question is unanswered, help us to find answer for this one

61. You work for an insurance company. Which machine learning project would add the most value for the company!

Answer

Correct Answer: Use machine learning to better predict risk.

Note: This Question is unanswered, help us to find answer for this one

62. How do machine learning algorithms make more precise predictions?

Answer

Correct Answer: The algorithms are better at seeing patterns in the data.

Note: This Question is unanswered, help us to find answer for this one

63. How is machine learning related to artificial intelligence?

Answer

Correct Answer: Machine learning is a type of artificial intelligence that relies on learning through data.

Note: This Question is unanswered, help us to find answer for this one

64. Why is naive Bayes called naive?

Answer

Correct Answer: It naively assumes that the predictors are independent from one another.

Note: This Question is unanswered, help us to find answer for this one

65. To predict a quantity value. use ___.

Answer

Correct Answer: Regression

Note: This Question is unanswered, help us to find answer for this one

66. You work for a power company that owns hundreds of thousands of electric meters. These meters are connected to the internet and transmit energy usage data in real-time. Your supervisor asks you to direct project to use machine learning to analyze this usage data. Why are machine learning algorithms ideal in this scenario?

Answer

Correct Answer: The algorithms would help your organization see patterns of the data.

Note: This Question is unanswered, help us to find answer for this one

67. What is an example of a commercial application for a machine learning system?

Answer

Correct Answer: A product recommendation system

Note: This Question is unanswered, help us to find answer for this one

68. ____ looks at the relationship between predictors and your outcome.

Answer

Correct Answer: Regression analysis

Note: This Question is unanswered, help us to find answer for this one

69. You work in a data science team that wants to improve the accuracy of its K-nearest neighbor result by running on top of a naive Bayes result. What is this an example of?

Answer

Correct Answer: Stacking

Note: This Question is unanswered, help us to find answer for this one

70. You want to identify global weather patterns that may have been affected by climate change. To do so, you want to use machine learning algorithms to find patterns that would otherwise be imperceptible to a human meteorologist. What is the place to start?

Answer

Correct Answer: Use unsupervised learning have the machine look for anomalies in a massive weather database.

Note: This Question is unanswered, help us to find answer for this one

71. Your company wants to predict whether existing automotive insurance customers are more likely to buy homeowners insurance. It created a model to better predict the best customers contact about homeowners insurance, and the model had a low variance but high bias. What does that say about the data model?

Answer

Correct Answer: It was consistently wrong.

Note: This Question is unanswered, help us to find answer for this one

72. In traditional computer programming, you input commands. What do you input with machine learning?

Answer

Correct Answer: Data

Note: This Question is unanswered, help us to find answer for this one

73. You work for an organization that sells a spam filtering service to large companies. Your organization wants to transition its product to use machine learning. It currently a list Of 250,00 keywords. If a message contains more than few of these keywords, then it is identified as spam. What would be one advantage of transitioning to machine learning?

Answer

Correct Answer: The product could find spam messages using far fewer keywords.

Note: This Question is unanswered, help us to find answer for this one

74. You are part of data science team that is working for a national fast-food chain. You create a simple report that shows trend: Customers who visit the store more often and buy smaller meals spend more than customers who visit less frequently and buy larger meals. What is the most likely diagram that your team created?

Answer

Correct Answer: Linear regression and scatter plots

Note: This Question is unanswered, help us to find answer for this one

75. Which of the following features or algorithms are supported by the Scikit—Learn tool?

Answer

Correct Answer: Classif‌ication
Model Selection

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

76. In relation to machine learning classif‌ication, which two of the following are the correct features of ID3 (Iterative Dischotomiser 3) algorithm?

Answer

Correct Answer: It supports back tracking search.

Note: This Question is unanswered, help us to find answer for this one

77. Which of the following solutions can be used for the noisy data classification problem of ID3 and C45 decision tree algorithm?

Answer

Correct Answer: Use Credal-C4.5 tree
Use enhanced algorithm with Taylor formula

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

78. The Amazon Machine Learning tool supports which of the following types of models?

Answer

Correct Answer: Binary classification

Note: This Question is unanswered, help us to find answer for this one

79. Which of the following are the advantages of the Naive Bayes algorithm used for classification?

Answer

Correct Answer: It is fast as compared to sophisticated methods.

Note: This Question is unanswered, help us to find answer for this one

80. Which of the following statements are correct about the Gradient Boosting classif‌ication technique?

Answer

Correct Answer: In this technique, training is done in parallel.
It is hard to tune.

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

81. In relation to machine learning, which of the following statements are correct about the TensorFIow library?

Answer

Correct Answer: TensorFlow is only supported by Google.

Note: This Question is unanswered, help us to find answer for this one

82. Which of the following are the correct features of the Random Forest algorithm used for classif‌ication?

Answer

Correct Answer: The real time prediction is fast.

Note: This Question is unanswered, help us to find answer for this one

83. In relation to machine learning classif‌ication algorithm, which of the following are the linear classif‌iers?

Answer

Correct Answer: Least square support vector machine
Random Forest

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

84. Which of the following options are the advantages of K-Nearest Neighbor (KNN) classif‌ication technique?

Answer

Correct Answer: Its computation complexity is very low.
It is easy to implement.
It is robust to noisy training data.

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

85. Which two of the following are the machine learning classification problems?

Answer

Correct Answer: Predicting the price of a shop based on area.
Predicting the number of copies of a book that will be sold next fortnight

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

86. Which of the following options are the machine learning tools for a command line interface?

Answer

Correct Answer: Waff‌les
WEKA Machine Learning Workbench

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

87. Which of the following options are the advantages of the Multilayer Perceptron?

Answer

Correct Answer: It can learn non-linear models.
It can learn models in real-time.

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

88. Which of the following statements are correct about the Shogun machine learning library?

Answer

Correct Answer: It is open-source.
It is cross-platform and API oriented.

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

89. In relation to machine learning, which of the following options are the toolkits for working with human language data?

Answer

Correct Answer: Gensim
NLTK

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

90. APls are included for which of the following options in TensorFlow?

Answer

Correct Answer: C++
Python

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

91. Which of the following frameworks can be used for cross-platform solutions?

Answer

Correct Answer: TensorFlow
Caffe2

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

92. In Convolutional Neural Networks, the input can be in which of the following formats?

Answer

Correct Answer: One-dimensional
Two-dimensional

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

93. In relation to machine learning classif‌ication algorithm, which of the following options are used by the decision tree for constructing a decision tree?

Answer

Correct Answer: Entropy
Information Gain
Try 1-2

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

94. Which of the following are the correct features of the KNIME tool for machine learning?

Answer

Correct Answer: It can integrate the code of programming languages such as C, C++, R, and Java, etc.
Its deployment and installation is very easy.

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

95. In machine learning, which of the following statements are correct about optical coherence tomography (OCT)?

Answer

Correct Answer: It has a very limited OCT imaging depth.
It is hard to interpret an OCT image.

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

96. The LibLinear library is written in which of the following languages?

Answer

Correct Answer: C
C++

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

97. Which two of the following statements are correct regarding classif‌ication, which is a machine learning technique?

Answer

Correct Answer: It uses known data in order to determine how new data is classif‌ied into a set of existing categories.
It is a form of supervised learning.

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

98. In relation to machine learning classif‌ication, which of the following are the correct features of the Stochastic Gradient Descent algorithm?

Answer

Correct Answer: It supports many loss functions and penalties for classif‌ication.
It is easy and eff‌icient to implement.

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

99. Which of the following options are the correct features of the PyTorch framework?

Answer

Correct Answer: It supports the data parallelism.
It supports distributed learning model.

Note: This question has more than 1 correct answers

Note: This Question is unanswered, help us to find answer for this one

100. Which of the following types of artif‌icial neural networks is/ are best suited for mapping the image data to an output variable?

Answer

Correct Answer: Convolutional Neural Networks (CNNS)

Note: This Question is unanswered, help us to find answer for this one

101.

Which of the following classif‌ication techniques should be used for the given tasks?

1. Selection of question pools

2. Prediction of software defects

3. Analysis of coal logistics customer

4. Thrombosis collagen diseases

Answer

Correct Answer:

C45 


Note: This Question is unanswered, help us to find answer for this one

102. Which of the following supervised learning algorithms is/are implemented by Apache Mahout?

Answer

Correct Answer: Naive Bayes classifiers

Note: This Question is unanswered, help us to find answer for this one

103. Which of the following classif‌ication algorithms should be used for the given scenario? The data is labeled and the number of samples is greater than 100k.

Answer

Correct Answer: Linear SVC

Note: This Question is unanswered, help us to find answer for this one

104. In relation to SVM classification algorithm. which of the following options is used for the binary classification?

Answer

Correct Answer: Sigmoid kernel

Note: This Question is unanswered, help us to find answer for this one

105. In data mining, which of the following clustering methods reflects spatial distribution of the data points?

Answer

Correct Answer: Model-based method

Note: This Question is unanswered, help us to find answer for this one

106. Which of the following formulae is used for correctly calculating the accuracy of the classification algorithms?

Answer

Correct Answer: Accuracy: (True Positive + True Negative) / Total Population

Note: This Question is unanswered, help us to find answer for this one

107. Which of the following interfaces is/are supported by Scikit—Learn tool?

Answer

Correct Answer: API

Note: This Question is unanswered, help us to find answer for this one

108. What is the FI-Score of Random Forest algorithm used for classification?

Answer

Correct Answer: 0.5224

Note: This Question is unanswered, help us to find answer for this one

109. What is the correct F1 score of the Random Forest algorithm of classif‌ication?

Answer

Correct Answer: 0.6275

Note: This Question is unanswered, help us to find answer for this one

110. Which of the following simulation model types contain(s)probability?

Answer

Correct Answer: Stochastic simulations

Note: This Question is unanswered, help us to find answer for this one

111. Can decision trees over f‌it data?

Answer

Correct Answer: Yes

Note: This Question is unanswered, help us to find answer for this one

112.

Which of the following algorithms has the given applications?

1. Scene classification

2. Induction motors fault diagnosis

3. Analog circuit fault diagnosis

4. Corporate financial distress prediction

Answer

Correct Answer:

SVM


Note: This Question is unanswered, help us to find answer for this one

113. Which of the following boosting algorithms uses the level-wise tree growth?

Answer

Correct Answer: Light GB

Note: This Question is unanswered, help us to find answer for this one

114. With respect to multilayer neural network, what does the neurons in the hidden layer correspond to?

Answer

Correct Answer: Non-linear latent variables

Note: This Question is unanswered, help us to find answer for this one

115. In data mining, which of the following is NOT a data reduction technique?

Answer

Correct Answer: Huffman

Note: This Question is unanswered, help us to find answer for this one

116.

Which of the following statements is/are correct?

Statement 1: In stochastic simulation environments, machine learning is performed by combining multiple transmutations.

Statement 2: Stochastic simulation is used for modelling a system whose operation can be directly captured by deterministic rules.

Answer

Correct Answer:

Statement 1 is correct.  


Note: This Question is unanswered, help us to find answer for this one

117.

Find the output of the following code, when executed in MATLAB.

A = [8 4 7 5 3]

isinteger(A)

isf‌loat(A)

isvector(A)

isscalar(A)


Answer

Correct Answer:

A =

8 4 7 5 3
ans = 0

ans = 1

ans =1

ans =      


Note: This Question is unanswered, help us to find answer for this one

118. The EIasticNet regression technique:

Answer

Correct Answer: does not have any limitations on the number of selected variables.

Note: This Question is unanswered, help us to find answer for this one

119.

Consider the following code to be executed in MATLAB.

m = roots([?., 8])

What will be the output?


Answer

Correct Answer:

 m = -4  


Note: This Question is unanswered, help us to find answer for this one

120.
Which Of the following statistical data mining techniques is used to predict a categorical response variable?

Answer

Correct Answer:

Factor analysis 


Note: This Question is unanswered, help us to find answer for this one

121.

What will be the output of the following code, when executed in MATLAB?

z = [6 9 4 3 5]:

polyval(z,3)


Answer

Correct Answer:

ans= 779


Note: This Question is unanswered, help us to find answer for this one

122.

In relation to machine learning classif‌ication, which of following options refers to the graphical model for probability associations between a set of variables?


Answer

Correct Answer:

Bayesian Network


Note: This Question is unanswered, help us to find answer for this one

123.

What will be the output of the following code, when executed in MATLAB?

X = 45;

Y = 21;

Z = bitor(X, Y)

Z = bitxor(X, Y)

Z = bitshift(X,-3)

Z = bitshift(X,4)


Answer

Correct Answer:

2:61

2:56

2:5

2:72



Note: This Question is unanswered, help us to find answer for this one

124.

In relation to classif‌ication in machine learning, which Of the following Options is the correct way for def‌ining the F1-Score?


Answer

Correct Answer:

F1-Score: (2 x Precision x Recall) / (Precision + Recall)     


Note: This Question is unanswered, help us to find answer for this one

125.

A target in machine learning is known as alan:

Answer

Correct Answer:

label


Note: This Question is unanswered, help us to find answer for this one

126.
In machine learning, random forests method is an example of which of the following feature selection methods?

Answer

Correct Answer:

Embedded method


Note: This Question is unanswered, help us to find answer for this one

127. An artificial neuron device consists of how many inputs and outputs?

Answer

Correct Answer: Many inputs and one output

Note: This Question is unanswered, help us to find answer for this one

128.

Which of the following are the applications of data mining?


(i)Science Exploration


(ii)Fraud Detection


(iii)Customer Retention


Answer

Correct Answer:

All (i), (ii)and (iii)


Note: This Question is unanswered, help us to find answer for this one

129.

What will be the output of the following code, when executed in MATLAB?

Z=[8471;7196;6429]

Z(3:3,1:3)


Answer

Correct Answer:

Z:

8 4 7 1

7 1 9 6

6 4 2 9

ans:
6 4 2  



Note: This Question is unanswered, help us to find answer for this one

130.

Which of the following machine learning tools works with large data volume and supports text mining and image mining through plugins?


Answer

Correct Answer:

KNIME 


Note: This Question is unanswered, help us to find answer for this one

131. The machine learning framework RapidMiner is written in which of the following programming languages?

Answer

Correct Answer: Java

Note: This Question is unanswered, help us to find answer for this one

132. Which of the following is incorrect about the feedforward artificial neural network topology?

Answer

Correct Answer: They do not have fixed inputs and outputs.

Note: This Question is unanswered, help us to find answer for this one

133. Which of the following is incorrect about the feedback artif‌icial neural network?

Answer

Correct Answer: Feedback networks are static.

Note: This Question is unanswered, help us to find answer for this one

134.

Any layer that the user wants to use.

In agent-based simulation, which of the following Inferential Theory of Learning (ITL)operations is used to modify knowledge by narrowing the reference set of a description?


Answer

Correct Answer:

Specialization 


Note: This Question is unanswered, help us to find answer for this one

135. In Multilayer Perceptrons, the predictions are made in which of the following layers?

Answer

Correct Answer: Output layer

Note: This Question is unanswered, help us to find answer for this one

136. In relation to machine learning. the XGBoost works for which of the following options?

Answer

Correct Answer: Tabular data

Note: This Question is unanswered, help us to find answer for this one

137. Which of the following statements is incorrect about Recurrent Neural Networks (RNNs)?

Answer

Correct Answer: They are non-deterministic.

Note: This Question is unanswered, help us to find answer for this one

138. Which of following is incorrect about modelica?

Answer

Correct Answer: It is a tool.

Note: This Question is unanswered, help us to find answer for this one

139. Which of the following is incorrect about linear regression?

Answer

Correct Answer: A dependent variable in linear regression is discrete.

Note: This Question is unanswered, help us to find answer for this one

140. In relation to machine learning framework, which of the following languages is used by Veles for performing automation and coordination between the nodes?

Answer

Correct Answer: Python

Note: This Question is unanswered, help us to find answer for this one

141. Which of the following is an advantage in logistic regression?

Answer

Correct Answer: Natural probabilistic view of class predictions.

Note: This Question is unanswered, help us to find answer for this one

142.

In the knowledge discovery process, which of the following steps is involved in retrieving data, relevant to the analysis task, from the database?


Answer

Correct Answer:

Data selection


Note: This Question is unanswered, help us to find answer for this one

143.

In relation to K-Nearest Neighbors (K-NN) algorithm, what effect does the small k value (neighborhood size) have on bias and variance?


Answer

Correct Answer:

Low Bias, High Variance


Note: This Question is unanswered, help us to find answer for this one

144. Which of the following types Of data analysis models is/are used to conclude continuous valued functions?

Answer

Correct Answer: Prediction

Note: This Question is unanswered, help us to find answer for this one

145. Which of the following machine learning frameworks works at the higher level of abstraction?

Answer

Correct Answer: Keras

Note: This Question is unanswered, help us to find answer for this one

146. Which of the following machine learning tools provides API for the neural networks?

Answer

Correct Answer: Keras.io

Note: This Question is unanswered, help us to find answer for this one

147. Simple linear regression is characterized by how many independent variables?

Answer

Correct Answer: One

Note: This Question is unanswered, help us to find answer for this one

148.

Which of the following machine learning tools supports vector machines, dimensionality reduction, and online learning, etc.?


Answer

Correct Answer:

Shogun 


Note: This Question is unanswered, help us to find answer for this one

149.

Which of the following methods is used to generate non-uniform random variates and uses multiple uniform [0,1] variables?


Answer

Correct Answer:

Acceptance-Rejection


Note: This Question is unanswered, help us to find answer for this one

150. Which of the following is NOT an example of bounded probability distribution?

Answer

Correct Answer: Logistic distribution

Note: This Question is unanswered, help us to find answer for this one

151. A multi-layer perceptron (MLP)is a:

Answer

Correct Answer: finite acyclic graph.

Note: This Question is unanswered, help us to find answer for this one

152. Which of the following is NOT a multi-class classif‌ier?

Answer

Correct Answer: Classif‌ication of spam and non-spam emails

Note: This Question is unanswered, help us to find answer for this one

153.

Which of the following tools is used for processing, analyzing and visualizing the large data sets and can provide native support for Apache Spark distributed computing?


Answer

Correct Answer:

Zeppelin 


Note: This Question is unanswered, help us to find answer for this one

154. Which of the following defines the F-score measure to assess the quality of text retrieval?

Answer

Correct Answer: F-score = recall x precision / (recall + precision)/ 2

Note: This Question is unanswered, help us to find answer for this one

155.

In the SVM classif‌ication approach, which of the following options is used for solving the issue of the low-sparse SVM classifier?


Answer

Correct Answer:

Cluster Support Vector Machine   


Note: This Question is unanswered, help us to find answer for this one

156.

Choose the answer to the following question from the options given in the image.

In machine learning, which of the given functions in the image is used to measure the size of vectors?