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?
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?
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?
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
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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)
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125.
A target in machine learning is known as alan:
Answer
Correct Answer:
label
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126.
In machine learning, random forests method is an example of which of the following feature selection methods?
Answer
Correct Answer:
Embedded method
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127. An artificial neuron device consists of how many inputs and outputs?
Answer
Correct Answer:
Many inputs and one output
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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)
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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
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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
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131. The machine learning framework RapidMiner is written in which of the following programming languages?
Answer
Correct Answer:
Java
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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.
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133. Which of the following is incorrect about the feedback artificial neural network?
Answer
Correct Answer:
Feedback networks are static.
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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
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135. In Multilayer Perceptrons, the predictions are made in which of the following layers?
Answer
Correct Answer:
Output layer
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136. In relation to machine learning. the XGBoost works for which of the following options?
Answer
Correct Answer:
Tabular data
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137. Which of the following statements is incorrect about Recurrent Neural Networks (RNNs)?
Answer
Correct Answer:
They are non-deterministic.
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138. Which of following is incorrect about modelica?
Answer
Correct Answer:
It is a tool.
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139. Which of the following is incorrect about linear regression?
Answer
Correct Answer:
A dependent variable in linear regression is discrete.
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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
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141. Which of the following is an advantage in logistic regression?
Answer
Correct Answer:
Natural probabilistic view of class predictions.
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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
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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
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144. Which of the following types Of data analysis models is/are used to conclude continuous valued functions?
Answer
Correct Answer:
Prediction
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145. Which of the following machine learning frameworks works at the higher level of abstraction?
Answer
Correct Answer:
Keras
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146. Which of the following machine learning tools provides API for the neural networks?
Answer
Correct Answer:
Keras.io
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147. Simple linear regression is characterized by how many independent variables?
Answer
Correct Answer:
One
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148.
Which of the following machine learning tools supports vector machines, dimensionality reduction, and online learning, etc.?
Answer
Correct Answer:
Shogun
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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
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150. Which of the following is NOT an example of bounded probability distribution?
Answer
Correct Answer:
Logistic distribution
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151. A multi-layer perceptron (MLP)is a:
Answer
Correct Answer:
finite acyclic graph.
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152. Which of the following is NOT a multi-class classifier?
Answer
Correct Answer:
Classification of spam and non-spam emails
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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
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154. Which of the following defines the F-score measure to assess the quality of text retrieval?