Learn vocabulary, terms, and more with flashcards, games, and other study tools. A) Characterization and Discrimination B) Classification and regression C) Selection and interpretation D) Clustering and Analysis Answer: C 5. Describe how data mining can help the company by giving specific examples of how techniques, such as clus-tering, classification, association rule mining, and anomaly detection can be applied. parallel processing in databases. Data Discretization b. This topic provides information that you need to know when connecting to an instance of SQL Server Analysis Services to create, process, deploy, or query data mining … experiments. In simplified, descriptive and yet accurate ways, it can be helpful to define individual groups and concepts. In this information age, because we believe that information leads to power and success, and thanks to sophisticated technologies such as computers, satellites, … 2. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and … Valid on new or test data with some degree of certainty Data Mining Functionalities 3. There are two main types of MCQ: those where there is only one correct answer and those where there is more than one possible answer. The data mining result is stored in another file. Involves working with known information The process of extracting valid, useful, unknown info from data and using it to make proactive knowledge driven business is called Data mining Which of the following activities is performed as part of data pre processing? ..... is a comparison of the general features of the target class data objects against the general features of objects from one or multiple contrasting classes. A. These data objects are outliers. These Data Mining Multiple Choice Questions (MCQ) should be practiced to improve the skills required for various interviews (campus interview, walk-in interview, company interview), placements, entrance exams and other … High amount of data in an infinite stream. Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. TF Structured and Unstructured Data Classification Cleared.txt, San Francisco State University • CS 112, University of North Texas, Dallas • COMPUTER MISC, Khan Academy Behavioral Review Only__P_S 6A_ Sensing the Environment.txt, Pir mehr Ali Shah Arid Agriculture University, Rawalpindi, Pir mehr Ali Shah Arid Agriculture University, Rawalpindi • IT CS600, Texas A&M University, -Central Texas • CISK 332, Copyright © 2021. Data mining has a vast application in big data to predict and characterize data. 9. answered Jun 10, 2016 by NubiKing . Data mining: 6 pts Discuss (shortly) whether or not each of the following activities is a data mining task. cluster analysis. A data warehouse is well equipped for providing data for mining for the following reasons: • Data mining requires data quality and consistency of input data and data … Which of the following is not applicable to Data Mining? Data Mining MCQs Questions And Answers. However, unlike … Data mining is a process that is useful for the discovery of informative and analyzing … Choose which data mining task is the most suitable for the following scenario: Given a set of n points or objects, and k, the expected number of outliers, find the top k objects that considerably dissimilar, exceptional or inconsistent with the remaining data On the basis of the kind of data to be mined, there are two categories of functions involved in Data Mining − Descriptive; Classification and Prediction; Descriptive Function. In other words, we can say that data mining is the procedure of mining knowledge from data. _____ is a summarization of the general characteristics or features of a target class of data. D. The process of obtaining, cleaning, organizing, relating, and cataloging source data is in the _____ activity of the BI process. c)It may not be useable. The disaster recovery plan (DRP) includes a hot site that is located sufficiently away from the main data center and will allow recovery in the event of a major disaster. ..... is a summarization of the general characteristics or features of a target class of data. A) content mining B) structure mining C) server mining D) usage mining E) data mining. 3. Easily understood by humans, 2. Data mining techniques statistics is a branch of mathematics that relates to … This refers to the observation for data items in a dataset that do not … 53) Which of the following is not a data mining functionality? Knowledge discovery in database – c. OLAP d. Business intelligence Which of the following is not a data pre-processing methods Select one: a. A. Functionality B. Data Stream Mining is t he process of extracting knowledge from continuous rapid data records which comes to the system in a stream. b)It may not exist. Course. You advise him that the use of secondary data has some potential problems. Database system can be classified according to different criteria such as data models, types of data, etc. The data resided in data warehouse is predictable with a specific interval of time and delivers information from the historical perspective. classification and prediction . Which of the following is not applicable to Data Mining? Review the accompanying lesson, Data Warehousing and Data Mining: Information for Business Intelligence, for further information. These class or concept definitions are referred to as class/concept descriptions. ..... is a summarization of the general characteristics or features of a target class of data. … This also generates new information about the data which we possess already. 1. Artificial intelligence(AI) — These systems perform analytical activities associated with human in… For example, it can organize and analyze data from IoT systems to enable the predictive maintenance of factory equipment or it can combine historical sales data with customer behaviors to predict future sales and patterns of demand. C) Selection and interpretation 4. DATA WAREHOUSE AND OLAP TECHNOLOGY: An Overview. Q27. This query is input to the system. Data mining requires a single, separate, clean, integrated, and self-consistent source of data. B) data warehouse view C) data source view D) business query view. Q20. C) Selection and interpretation 4. A. Functionality B. Data Mining System, Functionalities and Applications: A Radical Review Dr. Poonam Chaudhary System Programmer, Kurukshetra University, Kurukshetra Abstract: Data Mining is the process of locating potentially practical, interesting and previously unknown patterns from a big volume of data. Potentially useful 4. Which of the following terms is used as a synonym for data mining? Another feature of time-variance is that once data is stored in the data warehouse then it cannot be modified, alter, or updated. It comprises elements of time explicitly or implicitly. These short solved questions or quizzes are provided by Gkseries. Which of the following is not a data mining functionality? Answer: The following equations can be used to compute the value of the coefficients β0 and β1.Using the following set of data, find the coefficients β0 and β1rounded to the nearest thousandths place and the predicted value of y when x is 10. This preview shows page 127 - 130 out of 323 pages. social media sites. A data mining process may uncover thousands of rules from a given data set, most of which end up being unrelated or uninteresting to users. C. Cleanse the data. Achieving the best results from data mining requires an array of tools and techniques. Data Stream Mining fulfil the following characteristics: Continuous Stream of Data. Data mining is categorized as: Predictive data mining: This helps the developers in understanding the characteristics that are not explicitly available. 1. Security and Social Challenges: Decision-Making strategies are done through data … … (B). B. ..... is a summarization of the general characteristics or features of a target class of data. Much like the real-life process of mining diamonds or gold from the earth, the most important task in data mining is to extract non-trivial nuggets from large amounts of data. Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Oracle Data Mining supports the scoring operation for clustering and feature extraction, both unsupervised mining functions. Using too large a value of lambda can cause your hypothesis to overfit the data C. Using a very large value of lambda cannot hurt the performance of your hypothesis. Answer: (A) Firms that are engaged in sentiment mining are analyzing data collected from (A). This set of multiple-choice questions – MCQ on data mining includes collections of MCQ questions on fundamentals of data mining techniques. Which of the following is not a data mining functionality? Data mining, because of many reasons, is really promising. D. Search the data. A) Data Characterization 5. is a subject-oriented, integrated, time-variant. social media sites. Define each of the following data mining functionalities: characterization, discrimination, association and correlation analysis, classification, regression, clustering, and outlier analysis. (a)Dividing the customers of a company according to their pro tability. A. Conformity B. Exploratory C. Confirmatory D. Explanatory 2 Points QUESTION 2 Which Function Is Used To Count The Number Of Characters In A String Field? Which of the following is true (a) The output of KDD is data (b) The output of KDD is Query (c) The output of KDD is Informaion ... Data mining database servers (b) Data warehouse database servers (c) Data mart database servers (d) Relational database servers. iv) Handling uncertainty, noise, or incompleteness of data. Easily understood by humans, 2. Suppose that you are employed as a data mining consultant for an In-ternet search engine company. Clustering: Similar to classification, clustering is the organization of data in classes. 1. Course Hero, Inc. A database may contain data objects that do not comply with the general behavior or model of the data. A) Data Characterization 5. ..... is a comparison of the general features of the target class data objects against the general features of objects … Monitoring and predicting failures in a hydropower plant b. Which of the following terms is used as a synonym for data mining? Oracle Data Mining does not support the scoring operation for association rules, another unsupervised function. Most data mining methods discard outliers as noise or exceptions. Which of the following is not one of them? data warehousing (C). Vendor consideration C. Compatibility D. All of the above Ans: D. 13. E. Organize and relate data. focus groups. Class/Concept Descriptions: Classes or definitions can be correlated with results. Validates some hypothesis that a user seeks to confirm A) Characterization and Discrimination B) Classification and regression C) Selection and interpretation D) Clustering and Analysis Answer: C) Selection and interpretation 54) ..... is a summarization of the general characteristics or features of a target class of data. Assignment 1. Note − These primitives allow us to communicate in an interactive manner with the data mining system. characteristic and discrimination. It works by scrutinizing information from different databases and closely understanding the customer to create effective marketing strategies. we do not … Adaptive system management is A. A data mining query is defined in terms of data mining task primitives. The methods include tracking patterns, classification, association, outlier detection, clustering, regression, and prediction. parallel processing in databases. The following are examples of … For example, if we classify a database according to the data model, then we may have a relational, transactional, object-relational, or data warehouse mining system. data warehousing (C). Which of the following issue is considered before investing in Data Mining? Give examples of each data mining functionality, using a real-life database that you are familiar with. 8) Your assistant wants to use secondary data exclusively for the current research project. Data cleansing and preparation— A step in which data is transformed into a form suitable for further analysis and processing, such as identifying and removing errors and missing data. 16. Which of the following statements about regularization is not correct? And the data mining system can be classified accordingly. State true or false "Operational metadata defines the structure of the data … Novel 5. In a data mining task when it is not … The data mining functionality are used for representing the patterns to be defined in the data mining task. Potentially useful 4. data mining assignment-1 discuss whether or not each of the following activities is data mining task. This process brings useful patterns and thus we can make conclusions about the data. Multiple choice questions. Obtain the data. is a summarization of the general characteristics or, is a comparison of the general features of the target, class data objects against the general features of objects from one or multiple, is the process of finding a model that describes and, 58. Which of the following is not a kind of data warehouse application? In No-coupling scheme, the data mining system does not utilize any of the database or data warehouse functions. Data mining is looking for patterns in extremely large data stores. This is an accounting calculation, followed by the application of a threshold. 1. ..... is a summarization of the general characteristics or features of a target class of data. Which of the following is not a data mining functionality A Characterization. Nowadays Data Mining and knowledge discovery are evolving a crucial technology for business and researchers in many domains.Data Mining is developing into established and trusted discipline, many still pending challenges have to be solved.. 1. It will scale the data between 0 and 1. The process helps companies to convert raw information into useful data. Data Warehouse b. Which of the following is not one of the techniques used in Web mining? Data Mining is an important analytic process designed to explore data.   Terms. outlier analysis. Which of the following is not a data mining functionality? Give examples of each data mining functionality, using a real-life database that you are familiar with. regression analysis (D). Using too large a value of lambda can cause your hypothesis to underfit the data. Which of the following is not a data mining functionality? DataMining means extra... Why DataMining can be used? Some of these challenges are given below. experiments. Data can be associated with classes or concepts. 2018/2019. Which of the following is NOT one of the functions of a data warehouse? These short objective type questions with answers are very important for Board exams as well as competitive exams. Vendor consideration C. Compatibility D. All of the above Ans: D. 13. A) Data Characterization 5. The analysis of outlier data is referred to as outlier mining. As data mining works on the structured data within the organization, it is particularly suited to deliver a wide range of operational and business benefits. Which of the following is true (a) The output of KDD is data (b) The output of KDD is Query (c) The output of KDD is Informaion (d) The output of KDD is useful information. regression analysis (D). It fetches the data from a particular source and processes that data using some data mining algorithms. 10. ..... is a comparison of the general features of the target class data objects against the general features of objects from one or multiple contrasting classes. It uses machine-learning techniques. We can classify a data mining system according to the kind of databases mined. Which of the following issue is considered before investing in Data Mining? However, in some applications such as fraud detection, the rare events can be more interesting than the more regularly occurring ones. (A). It uses machine-learning techniques. The descriptive function deals with the general properties of data in the database. Data Mining Task Primitives. Fraud Detection: Frauds and malware is one of the most dangerous threats on the internet. Association models are built on a population of interest to obtain information about that population; they cannot be applied to separate data. Assignment-1. Adaptive system management is A. Chapter I: Introduction to Data Mining: By Osmar R. Zaiane: Printable versions: in PDF and in Postscript : We are in an age often referred to as the information age. Min Max is a data normalization technique like Z score, decimal scaling, and normalization with standard deviation.It helps to normalize the data. ..... is a comparison of the general features of the target class data objects against the general features of objects … Start studying GCSS-Army Data Mining Test 1. 2. Clustering . Define each of the following data mining functionalities: characterization, discrimination, association and correlation analysis, classification, regression, clustering, and outlier analysis. Try the multiple choice questions below to test your knowledge of this chapter. Which of the following is not a data mining functionality? Which of the following activities is NOT a data mining task? d)It may not be relevant a)It may not be current. A. Functionality B. the major functionality of the data mining . Data Mining is defined as extracting information from huge sets of data. It is almost a kind of crime that is increasing day after day. Which of the following is not a component of a data warehouse? A) Metadata B) Current detail data C) Lightly summarized data D) Component Key. if the answer is yes, then also specify which one of the. A) Information processing B) Analytical processing C) Data mining In No-coupling scheme, the data mining system does not utilize any of the database or data warehouse functions.
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