Assignment Week 4.docx Assignment University of The Cumberlands Intro to Data Mining

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Assignment Week 4.docx Assignment University of The Cumberlands Intro to Data Mining 1) What were the traditional methods of data collection in the transit system? The traditional metho... ds of data collection in the transit system were the following: ï‚· Human surveyors or direct observation: Human surveyors are either in the form of a video or in the terrain. ï‚· Invasive modes: The invasive method for collecting data may involve the magnetic sensors or the piezo sensors. ï‚· Radars: Data can be collected and gathered with the help of radars. ï‚· Machine Vision: Data can also be collected by analyzing the images. These images are properly viewed with the help of some machines vision. ï‚· Interviews: They are conducted by involving the open-ended questions or survey-based questions. 2) Why are the traditional methods insufficient in satisfying the requirement of data collection? Now the case study is referred to as a process which is vague. You may not generalize the data with respect to many people of similar group. Then you cannot get hold on the researcher. Letter and other documents are allowed in the case study method while all data is documented unorder to either impress or influence the reader. It is always yourself oriented i.e. it always comes out the way you want to depict. Due to the possible outcome of distortion the case study can be meaningless or worthless as it is always self-oriented. The collect. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . .. .. . . . . . . . . . . . . . . . . . .. . . . . [Show More]

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