Problem 1: Differentiate between the following terms:
a. classification and clustering
b. classification and prediction
c. data warehouse and database
d. data mining and OLAP
e. data mining and machine learning
Problem 2:
Discuss whether or not each of the following activities is a data mining task.
(a) Monitoring the heart rate of a patient for abnormalities.
(b) Computing the total sales of a company.
(c) Sorting a student database based on student identification numbers.
(d) Predicting the outcomes of tossing a (fair) pair of dice.
(e) Monitoring seismic waves for earthquake activities.
Problem 3: Fisher's iris data (download the IRIS dataset from https://archive.ics.uci.edu/ml/datasets/Iris) consists of measurements on the sepal length, sepal width, petal length, and petal width of 150 iris specimens. There are 50 specimens from each of three species.
Use SPSS to answer the following questions:
a. Visualize and interpret the relationship between the two sepal variables, sepal length and sepal width. Provide the scatterplot that you created to visualize the data along with your interpretation. When you plot the data, you may want to use different colors/signs for representing the data points belonging to the different three class species. Do you think that a classification algorithm will be successful in classifying the data with respect to these two variables? Justify your answer.
b. Repeat part a. for the petal variables.
c. Draw the histograms of the four variables and interpret the distributions of each one of the four variables.
d. Determine if there are any outliers in the data with respect to the sepal length.
e. Repeat d. for the petal length.