Data mining is the process of sorting through large data sets to identify repetitive patterns between variables. An important goal of data mining is to uncover hidden patterns and discover relationships in data that can be used to train machine learning algorithms and make predictions that impact businesses. Data mining, which is a subset of analytics, uses mathematical algorithms to examine large data sets and uncover previously unidentified sequences and correlations. It differs from other types of statistical analysis in that, rather than testing a previously established hypothesis, data mining slices and dices data in many different ways in an effort to reveal something useful. For example, association rules can be used to analyze data in a database for frequent if/then patterns. Support and confidence criteria can then be used to rank the most important relationships within the data. (Support is how frequently the items appear in the database, while confidence is the number of times if/then statements are accurate.) Continue reading... Take today's Pop Quiz! Answers are below 1. What do you call a value that can change, depending on conditions or on information passed to the program? a. variable b. change agent Answer 2. What type of analysis involves collecting and interpreting data to uncover patterns and trends? a. statistical analysis b. empirical analysis Answer 3. Data __________ is a technique used in statistical analysis to identify patterns and trends in a larger data set. a. sampling b. dredging Answer 4. What do you call it when you break a body of information down into smaller parts or examine it from different viewpoints so that you can understand it better? Answer 5. _______________ is a statistical measure that indicates the extent to which two or more variables fluctuate in relation to each other. a. Correlation b. Context Answer |
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