mining quiz

how much do you actually know about mining? - proprofs quiz

Do you really know what mining is all about? Have you ever seen the mining process? If not, then take this quiz to test your knowledge and learn about the mining process and methods of extraction. Mining is a lengthy extraction process of minerals like iron ore, metals, coal, gemstones, limestone etc. Even petroleum, water, and gold is the part of the mining process which is time taking. Read the questions carefully and answer. So, let's try out the quiz. All the best!

300+ top data mining multiple choice questions and answers

3. Some telecommunication company wants to segment their customers into distinct groups in order to send appropriate subscription offers, this is an example of A. Supervised learning B. Data extraction C. Serration D. Unsupervised learning Ans: D

5. You are given data about seismic activity in Japan, and you want to predict a magnitude of the next earthquake, this is in an example of A. Supervised learning B. Unsupervised learning C. Serration D. Dimensionality reduction Ans: A

6. Assume you want to perform supervised learning and to predict number of newborns according to size of storks population (http://www.brixtonhealth.com/storksBabies.pdf), it is an example of A. Classification B. Regression C. Clustering D. Structural equation modeling Ans: B

A. Infrastructure, exploration, analysis, interpretation, exploitation B. Infrastructure, exploration, analysis, exploitation, interpretation C. Infrastructure, analysis, exploration, interpretation, exploitation D. Infrastructure, analysis, exploration, exploitation, interpretation Ans: A

13. Adaptive system management is A. It uses machine-learning techniques. Here program can learn from past experience and adapt themselves to new situations B. Computational procedure that takes some value as input and produces some value as output. C. Science of making machines performs tasks that would require intelligence when performed by humans D. none of these Ans: A

14. Bayesian classifiers is A. A class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory. B. Any mechanism employed by a learning system to constrain the search space of a hypothesis C. An approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation. D. None of these Ans: A

15. Algorithm is A. It uses machine-learning techniques. Here program can learn from past experience and adapt themselves to new situations B. Computational procedure that takes some value as input and produces some value as output C. Science of making machines performs tasks that would require intelligence when performed by humans D. None of these Ans: B

16. Bias is A.A class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory B. Any mechanism employed by a learning system to constrain the search space of a hypothesis C. An approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation. D. None of these Ans: B

17. Background knowledge referred to A. Additional acquaintance used by a learning algorithm to facilitate the learning process B. A neural network that makes use of a hidden layer C. It is a form of automatic learning. D. None of these Ans: A

18. Case-based learning is A. A class of learning algorithm that tries to find an optimum classification of a set of examples using the probabilistic theory. B. Any mechanism employed by a learning system to constrain the search space of a hypothesis c. An approach to the design of learning algorithms that is inspired by the fact that when people encounter new situations, they often explain them by reference to familiar experiences, adapting the explanations to fit the new situation. D. None of these Ans: C

19. Classification is A. A subdivision of a set of examples into a number of classes B. A measure of the accuracy, of the classification of a concept that is given by a certain theory C. The task of assigning a classification to a set of examples D. None of these Ans: A

20. Binary attribute are A. This takes only two values. In general, these values will be 0 and 1 and .they can be coded as one bit B. The natural environment of a certain species C. Systems that can be used without knowledge of internal operations D. None of these Ans: A

21. Classification accuracy is A. A subdivision of a set of examples into a number of classes B. Measure of the accuracy, of the classification of a concept that is given by a certain theory C. The task of assigning a classification to a set of examples D. None of these Ans: B

22. Biotope are A. This takes only two values. In general, these values will be 0 and 1 and they can be coded as one bit. B. The natural environment of a certain species C. Systems that can be used without knowledge of internal operations D. None of these Ans: B

23. Cluster is A. Group of similar objects that differ significantly from other objects B. Operations on a database to transform or simplify data in order to prepare it for a machine-learning algorithm C. Symbolic representation of facts or ideas from which information can potentially be extracted D. None of these Ans: A

24. Black boxes are A. This takes only two values. In general, these values will be 0 and 1 and they can be coded as one bit. B. The natural environment of a certain species C. Systems that can be used without knowledge of internal operations D. None of these Ans: C

26. Data mining is A. The actual discovery phase of a knowledge discovery process B. The stage of selecting the right data for a KDD process C. A subject-oriented integrated time variant non-volatile collection of data in support of management D. None of these Ans: A

28. Data independence means A. Data is defined separately and not included in programs B. Programs are not dependent on the physical attributes of data. C. Programs are not dependent on the logical attributes of data D. Both (B) and (C). Ans: D

36. Inductive logic programming is A. A class of learning algorithms that try to derive a Prolog program from examples B. A table with n independent attributes can be seen as an n-dimensional space C. A prediction made using an extremely simple method, such as always predicting the same output D. None of these

37. Machine learning is A. An algorithm that can learn B. A sub-discipline of computer science that deals with the design and implementation of learning algorithms C. An approach that abstracts from the actual strategy of an individual algorithm and can therefore be applied to any other form of machine learning. D. None of these

38. Projection pursuit is A. The result of the application of a theory or a rule in a specific case B. One of several possible enters within a database table that is chosen by the designer as the primary means of accessing the data in the table. C. Discipline in statistics that studies ways to find the most interesting projections of multi-dimensional spaces D. None of these

40. Statistical significance is A. The science of collecting, organizing, and applying numerical facts B. Measure of the probability that a certain hypothesis is incorrect given certain observations. C. One of the defining aspects of a data warehouse, which is specially built around all the existing applications of the operational data D. None of these

41. Multi-dimensional knowledge is A. A class of learning algorithms that try to derive a Prolog program from examples B. A table with n independent attributes can be seen as an n-dimensional space C. A prediction made using an extremely simple method, such as always predicting the same output. D. None of these

43. Query tools are A. A reference to the speed of an algorithm, which is quadratically dependent on the size of the data B. Attributes of a database table that can take only numerical values. C. Tools designed to query a database. D. None of these

44. Operational database is A. A measure of the desired maximal complexity of data mining algorithms B. A database containing volatile data used for the daily operation of an organization C. Relational database management system D. None of these

45. Prediction is A. The result of the application of a theory or a rule in a specific case B. One of several possible enters within a database table that is chosen by the designer as the primary means of accessing the data in the table. C. Discipline in statistics that studies ways to find the most interesting projections of multi-dimensional spaces. D. None of these

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data mining quiz data mining course - proprofs quiz

Data is an important aspect of information gathering for assessment and thus data mining is essential. Through the quiz below you will be able to find out more about data mining and how to go about it. Take it up.