Data Mining
Chapter 1 Exercises
1. What is data mining? In your answer, address the following:
Data mining refers to the process or method that extracts or \mines" interesting knowledge or patterns from large amounts of data.
(a) Is it another hype?
Data mining is not another hype. Instead, the need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. Thus, data mining can be viewed as the result of the natural evolution of information technology.
(b) Is it a simple transformation or application of technology developed from databases, statistics, machine learning, and pattern recognition?
No. Data mining is more than a simple transformation of technology developed from databases, statistics, and machine learning. Instead, data mining involves an integration, rather than a simple transformation, of techniques from multiple disciplines such as database technology, statistics, machine learning, high-performance computing, pattern recognition, neural networks, data visualization, information retrieval, image and signal processing, and spatial data analysis..
(c) We have presented a view that data mining is the result of the evolution of database technology.
Do you think that data mining is also the result of the evolution of machine learning research?
Can you present such views based on the historical progress of this discipline? Do the same for the fields of statistics and pattern recognition.
(d) Describe the steps involved in data mining when viewed as a process of knowledge discovery
The steps involved in data mining when viewed as a process of knowledge discovery are as follows: * Data cleaning, a process that removes or transforms noise and inconsistent data * Data integration, where multiple data sources may be combined * Data selection, where data relevant to the analysis task are retrieved from the database * Data transformation, where data are
1. What is data mining? In your answer, address the following:
Data mining refers to the process or method that extracts or \mines" interesting knowledge or patterns from large amounts of data.
(a) Is it another hype?
Data mining is not another hype. Instead, the need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. Thus, data mining can be viewed as the result of the natural evolution of information technology.
(b) Is it a simple transformation or application of technology developed from databases, statistics, machine learning, and pattern recognition?
No. Data mining is more than a simple transformation of technology developed from databases, statistics, and machine learning. Instead, data mining involves an integration, rather than a simple transformation, of techniques from multiple disciplines such as database technology, statistics, machine learning, high-performance computing, pattern recognition, neural networks, data visualization, information retrieval, image and signal processing, and spatial data analysis..
(c) We have presented a view that data mining is the result of the evolution of database technology.
Do you think that data mining is also the result of the evolution of machine learning research?
Can you present such views based on the historical progress of this discipline? Do the same for the fields of statistics and pattern recognition.
(d) Describe the steps involved in data mining when viewed as a process of knowledge discovery
The steps involved in data mining when viewed as a process of knowledge discovery are as follows: * Data cleaning, a process that removes or transforms noise and inconsistent data * Data integration, where multiple data sources may be combined * Data selection, where data relevant to the analysis task are retrieved from the database * Data transformation, where data are