The U.S. Supreme Court has ruled that if management rejects a union’s proposal on grounds of inability to pay, ________________.

Which season(s) have days with the shortest average daylight? 

Which season(s) have days with the longest average daylight? 

Consider the following data points and their class labels: , , , , . We want to use the distance weighted 3-NN classification with this data.  Each point at a distance of d has a vote of (1/d) for predicting thee class label.   (a) (8) For the query point (5, 4, 4) find and report the data points in its 3-nearest-neighbor list, their weights for decision, and the class label that should be assigned to this query point.     (b) (6) What is gained and what is lost when we increase the value of K in a K-NN classifier?

(10) Consider the context of selecting the best attribute for decision tree construction. Explain briefly the difference between “information gain” and “gini ratio” metrics for selecting the best attributes. Do not write any formulas. Explain in a language only. 

I want to create an ensemble of seven decision trees, using bagging, for a training dataset.  (a) (8) Write briefly the steps you will use to generate this ensemble.   (b) (4) Why do you think an ensemble generally works better than a single decision tree?

Consider the following three data vectors. D1: (5, 6, 7, 9), D2:(6, 9, 10, 14), and D3: (4, 6, 2, 3). (a) (3) What are the Manhattan distances for the data-point pairs: D1-D2: D1-D3: D2-D3: (b) (5) What are the cosine similarities for the data-point pairs: D1-D2: D1-D3: D2-D3: (c) (2) Which two pints are the closest as per the Manhattan distance?   (d) (2) Which two points are the closest as per the Cosine similarity?

Discuss whether or not each of the following activitiy is a data miningtask.   Monitoring the heart rate of a patient for abnormalities.

(5) What is a kernel-trick and how does it help us in designing a non-linear SVM?   (5) What is the advantage of a Non-Linear SVM over a Linear-SVM?

You are approached by the marketing director of a local company, who believes that he has devised a foolproof way to measure customer satisfaction.He explains his scheme as follows: “It’s so simple that I can’t believe that no one has thought of it before. I just keep track of the number of customer complaints about each product. I read in a data mining book that counts are ratio attributes, and so, my measure of product satisfaction must be a ratio attribute. But when I rated the products based on my new customer satisfaction measure and showed them to my boss, he told me that I had overlooked the obvious and that my measure was worthless. I think that he was just mad because our best-selling product had the worst satisfaction since it had the most complaints. Could you help me set him straight?”   What can you say about the attribute type of the original product satisfaction attribute?