Data Mining Assignment 1

# Data Mining Assignment 1 - CSCE 5380 Data Mining Assignment...

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CSCE 5380 Data Mining Assignment 1: Exploring Data Wasana Santiteerakul 1. Discuss whether or not each of the following activities is a data mining task. a. Dividing the customers of a company according to their gender. ANS This activity is not a data mining task because it can be done by using a simple database query. b. Dividing the customers of a company according to their profitability. ANS This activity is not a data mining. If profitability of each customer is one of the attributes in customer records, using a threshold can divide the customers according to their profitability. c. Computing the total sales of a company. ANS This activity is not a data mining task because the total sales can be computed by using simple calculations. d. Sorting a student database based on student identification numbers. ANS This activity is not a data mining task because it is a simple database algorithm. e. Predicting the outcomes of tossing a (fair) pair of dice. ANS This activity is not a data mining task because predicting the outcome of tossing a fair pair of dice is a probability calculation, which doesn’t have to deal with large amount of data or use complicate calculations or techniques. f. Predicting the future stock price of a company using historical records. ANS This activity is a data mining task. Historical records of stock price can be used to create a predictive model called regression, one of the predictive modeling tasks that is used for continuous variables. g. Monitoring the heart rate of a patient for abnormalities. ANS This activity is a data mining task called anomaly detection. By observing the heart rate of the patient, this data mining task can identify the abnormalities if the characteristics of the heart rate are different from normal observations. h. Monitoring seismic waves for earthquake activities. ANS This activity is a data mining task. i. Extracting the frequencies of a sound wave.

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ANS This activity is not a data mining task because major categories of data mining tasks consist of predictive tasks and descriptive tasks. However, this activity may be considered as a data preprocessing to prepare suitable data before implementing data mining tasks. 2. Classify the following attributes as binary, discrete, or continuous. Also classify them as qualitative (nominal or ordinal) or quantitative (interval or ratio). Some cases may have more than one interpretation, so briefly indicate your reasoning if you think there may be some ambiguity. a. Time in terms of AM or PM. ANS Binary, qualitative, ordinal b. Brightness as measured by a light meter. ANS Continuous, quantitative, ratio c. Brightness as measured by people’s judgments. ANS Discrete, qualitative, ordinal d. Angles as measured in degrees between 0 and 360. ANS
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## This document was uploaded on 02/13/2010.

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Data Mining Assignment 1 - CSCE 5380 Data Mining Assignment...

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