MIS 450 | Complete Solution

Answer question with minimum of 200 words

Question 1
After reviewing Chapter 6 of your text, provide an example of an association rule from the market basket domain that satisfies each of the following conditions. Also, describe whether such rules are subjectively interesting. A pattern is subjectively interesting if it contradicts the expectation of a user and if it is actionable.
1.    A rule that has high support and high confidence
2.    A rule that has reasonably high support but low confidence
3.    A rule that has low support and low confidence
4.    A rule that has support and high confidence

Question 2
Clusters of documents can be summarized by finding the top terms (words) for the documents in the cluster, e.g., by taking the most frequent k terms, where k is constant, say 10, or by taking all terms that occur more frequently than a specified threshold. Suppose that K-means is used to find clusters of both documents and words for a document data set.
•    How might a set of term clusters defined by the terms in a document cluster differ from the word clusters found by clustering the terms with K-means?
•    How could term clustering be used to define clusters of documents?

Question 3
Consider a group of documents that has been selected from a much larger set of diverse documents so that the selected documents are as dissimilar from one another as possible. If we consider documents that are not highly related (connected, similar) to one another as being anomalous, then all of the documents that we have selected might be classified as anomalous. Discuss whether it is possible for a data set to consist only of anomalous objects, or if it is an abuse of the terminology?

Question 4
When a comprehensive training set is available, a supervised anomaly detection technique can typically outperform an unsupervised anomaly technique when performance is evaluated using measures such as the detection and false alarm rate. However, in some cases, such as fraud detection, new types of anomalies are always developing. Performance can be evaluated according to the detection and false alarm rates because it is possible to determine whether an object (transaction) is anomalous. Discuss the relative merits of supervised and unsupervised anomaly under such conditions.

Question 5
Reflect on this course. What will stick with you? What did you find most challenging? How will you use this newfound knowledge in your current and future career?