ISYE 6501 Midterm 1 Questions and Answers 100 Pass

Midterm Study Material ISYE 6501 | Full Answer Key Verified What do descriptive questions ask? - answer - What happened? (e.g., which customers are most alike) What do predictive questions ask? - answer - What will happen? (e.g., what will Google's stock price be?) What do prescriptive questions ask? - answer - What action(s) would be best? (e.g., where to put traffic lights) What is a model? - answer - Real-life situation expressed as math. What do classifiers help you do? - answer - differentiate What is a soft classifier and when is it used? - answer - In some cases, there won't be a line that separates all of the labeled examples. So we use a classifier that minimizes the number of mistakes. What does it mean when the classifier/decision boundary is almost parallel to the vertical x-axis? - answer - The horizontal attribute is all that is needed. What does it mean when the classifier/decision boundary is almost parallel to the horizontal y-axis? - answer - The vertical attribute is all that is needed. What is time-series data? - answer - The same data recorded over time often recorded at equal intervals What is quantitative data? - answer - Number with a meaning: higher means more, lower means less (e.g., age, sales, temperature, income) What is categorical data? - answer - Numbers w/o meaning (e.g., zip codes), non-numeric (e.g., hair color), binary data (e.g., male/female, yes/no, on/off) Which of these is time series data? A. The average cost of a house in the United States every year since 1820 B. The height of each professional basketball player in the NBA at the start of the season - answer - A Which of these is structured data? A. The contents of a person's Twitter feed B. The amount of money in a person's bank account - answer - B What is structured data? - answer - Data that can be stores in a structured way What is unstructured data? - answer - Data that is not easily described and stored (e.g., written text) A survey of 25 people recorded each person's family size and type of car. Which of these is a data point? A. The 14th person's family size and car type B. The 14th person's family size C.The car type of each person - answer - A. A data point is all the information about one observation The farther the wrongly classified point is from the line ___ - answer - The bigger the mistake we've made The term including the margin gets larger so the importance of a large margin out weights avoiding mistakes and classifying known data samples. - answer - As lambda gets larger That term also drops towards zero, so the importance of minimizing mistakes and classifying known data points outweighs having a large margin. - answer - As lambda drops towards zero What can SVMs be used for - answer - to find a classifier with maximum seperation or margin between the two sets of points? When to use SVM? - answer - If it's impossible to avoid classification errors, SVM can find a classifier that trades off reducing errors and enlarging the margin. Error for data point j - answer - What does this formula describe? Total error - answer - What does this formula describe ? To maximize the distance between the two lines what do we need to minimize? - answer - m_j 1 - answer - What value do we give for more costly errors Giving a bad loan is twice as costly as withholding a good loan? - answer - What does this mean in the context of giving a loan? m_j 1 - answer - What value do we give for less costly errors? Why is it important to scale our data when using SVM? - answer - We're looking to minimize the sum of the squares of the coefficients, but if our data has very different scales a small change in one could swamp a huge change in the other. what does it signify when a coefficient for a classifier is close to zero - answer - it means the corresponding attribute is probably not relevant What do kernel methods allow for in SVMs - answer - nonlinear classifiers What is the common range for scaled data?