Which algorithm is most closely associated with association rule mining and market basket analysis?
- A.Apriori
- B.k-means
- C.Dijkstra
- D.Quicksort
Correct answer
Explanation
The correct answer is A, Apriori. The Apriori algorithm first finds the sets of items that appear together often enough to pass a support threshold, using the rule that any subset of a frequent set must itself be frequent, and then turns those frequent sets into rules measured by confidence. This is the method behind market basket analysis, where a store learns which goods are bought together. Option B is wrong because k-means is a clustering algorithm: it groups similar records around k centres and is unsupervised, but it produces no rules. Option C is wrong because Dijkstra's algorithm finds the shortest path in a graph and belongs to network problems. Option D is wrong because quicksort merely arranges records in order and is a sorting algorithm, with no role in finding patterns.
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Practice Questions
View allA central repository of information that can be analyzed to make more informed decisions is known as:
- A.Data mining
- B.Data storing
- C.Data sorting
- D.Data warehouse
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A data warehouse is exactly that, a central store into which data from many operational systems is extracted, cleaned and loaded so that it can be analysed for decision making.
Read the full explanation →Which of the following statement(s) is/are correct regarding On-Line Transaction Processing (OLTP)? I. Responses to the user inquiry are immediate. II. The associated cost is economical with efficient utilization of resources. III. The database is always up-to-date.
- A.Only II
- B.I and III
- C.I and II
- D.Only III
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On-Line Transaction Processing is the mode in which a bank counter, a railway booking window or a payment gateway works: each transaction is processed the moment it is entered, so the response to the user is immediate, and every committed transaction is written at once, so the database always reflects…
Read the full explanation →Which of the following is NOT one of the three Vs of big data?
- A.Volume
- B.Velocity
- C.Variety
- D.Virtualisation
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Virtualisation is the technique of running several logical machines on one physical machine and belongs to the chapter on cloud computing, not to the definition of big data.
Read the full explanation →In Hadoop, which component is responsible for storing data across the machines of a cluster?
- A.MapReduce
- B.HDFS
- C.YARN
- D.Hive
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It splits a large file into fixed-size blocks, 128 megabytes by default in current versions, scatters those blocks over the machines of the cluster and keeps more than one copy of each block so that the failure of a machine does not lose data.
Read the full explanation →Data mining is best described as which step of the knowledge discovery process?
- A.The collection of raw data from sensors
- B.The step that finds patterns in prepared data
- C.The backing up of a database
- D.The printing of a management report
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In the process called Knowledge Discovery in Databases, or KDD, the stages run from selection of the relevant data, through cleaning and preprocessing, to transformation, then data mining, and finally interpretation and evaluation of what was found.
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