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CS 4407 - Data Mining and Machine Learning - Study || A+ Score
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True or False: Data Mining can be said to be a process designed to detect patterns in data sets. correct answers True True or False: In unsupervised learning, the learning algorithm must be trained using data attributes that have been paired with an outcome variable. correct answers False True or False: Unsupervised learning involves building a statistical model for predicting, or estimating an output based upon one or more inputs. correct answers False Regression analysis involves developing a model where one or more inputs are used to predict an output variable. Regression, in this context, represents what kind of learning. correct answers Supervised learning Assuming that we have a data set that includes sales data for every customer over the course of several years and we wanted to use this data to predict future sales which would be the most appropriate technique to investigate? correct answers Regression Assume that you had a variety of data including medical history, diet, heredity factors on individuals who developed cancer and you wanted to use this data to determine whether a person is likely to develop cancer. Which technique would be the most promising to start with? correct answers Classification Which of the following is an example of an unsupervised learning algorithm? correct answers K- Means True or False: A predication outcome variable must be categorical? correct answers False
Which of the following is NOT a machine learning technique? correct answers Linear Components Analytics True or False: In a supervised learning model, Bias refers to the error that is introduced from the assumptions of the data analyst. correct answers False The objective of ________ is to identify valid novel and potentially useful, and understandable correlations and patterns in existing data. correct answers data mining Which of the following is an example of a NOSQL Analytics database? correct answers Cassandra What does ETL stand for? correct answers Extract transform load True or False: In a data warehouse, unidimensional data is stored in a star schema format. correct answers False The term OLAP stands for? correct answers Online Analytical Processing A database where all of the values for a particular column are stored contiguously is called? correct answers Column-oriented storage True or False: The snowflake schema differs from the star schema in that the table holding the dimensional data are normalized. correct answers True True or False: Map/Reduce refers to an optimized approach to process SQL queries. correct answers False
m = 0. y = 6. Which command will provide descriptive statistics for the Boston data frame? correct answers summary(Boston) True or False: In the KNN algorithm, a small value for K provides the most flexible fit (low bias/high variance). correct answers True True or False: The fix() function identifies values that contain data within a data frame that are inconsistent and automatically corrects these values. correct answers False Residual plots are a useful tool for identifying: correct answers Non-linearity A linear regression model is expressed as y ≈ β0+ β1x where β0 is the intercept and β1 is the slope of the line. The following equations can be used to compute the value of the coefficients β and β1. Using the following set of data, find the coefficients β0 and β1rounded to the nearest thousandths place and the predicted value of y when x is 10.{(-1 , 0), (0 , 2), (1 , 4), (2 , 5)} correct answers β0 = 1. β1 = 1. y = 18. The values of x and their corresponding values of y are shown in the table below, identify the linear regression model in the form y=mx+b and report the values of m(slope) and b(intercept) as well as the estimated value of y when the value of x is 10. x 0 1 2 3 4 y 2 3 5 4 6 correct answers b = 2.
m = 0. y = 11. True or False: The library() function lists all of the libraries that are loaded into memory within R correct answers False True or False: Logistic regression can be used to predict a continuous variable. correct answers False A farmer's yield of corn is expressed as a linear regression model based upon the input variable which is the number of days of sunlight during the growing season. The model is express as Y = mX + b where Y is the estimated corn yield in bushels per acre, m = 1.38 and b = 42. Assuming that during the growing season it is predicted that there will be 67 days of sun, what will the corn yield be in bushels per acre? correct answers 134. True or False: The following data plot represents data that is linearly separable? (Everything is scattered) correct answers False What R command could we use to generate a scatterplot diagram of our data to determine if it forms a linear pattern that would be suitable for linear regression or a non-linear pattern that would require some other technique? correct answers plot() Which of the following is an example of a parametric approach. correct answers Linear Regression The income of a company that produces disaster equipment has been expressed as a linear regression model based upon the input variable which is the number of hurricanes projected for the upcoming hurricane season. The model is express as Y = mX + b where Y is the estimated sales in millions of dollars, m = .76 and b = 5. Assuming that the weather service is predicting 6 hurricanes during the season what are the sales in millions of dollars expected to be? correct answers 9.
True/False: Shared nothing architectures distribute the processing of queries to access large volumes of data and provide near linear scalability in both storage volume and query performance. correct answers True When using a relational database engine as the backend for analytics processing, the acronym _____ is used to describe it. correct answers ROLAP Assume that you had a variety of data including medical history, diet, heredity factors on individuals who developed cancer and you wanted to use this data to determine whether a person is likely to develop cancer. Which technique would be the most promising to start with? correct answers Classification Assuming you have a linear model in which the value of m is .05 and the value of b is 10 that explains the relationship between income and credit extended. If income is 50,000, what credit will be extended? correct answers 2510 True/False: A linear regression model can be used to predict categorical data values. correct answers False Assume that you have a data set which produces the following data plot. You wish to predict if a new case would be a 'red' case as opposed to a 'blue' case based upon the input attribute data. Which technique should you use? (Red points scattered on top, blue points scattered on bottom) correct answers Logistic Regression True/False: A regression model has a R2 statistic of .15. This indicates that the regression model is NOT a good fit and does a poor job of predicting the outcome based upon the input variables. correct answers True True/False: Supervised learning features both input variables or attributes and an output or predicted variable. correct answers True
True/False: According to our textbook, residual plots are a useful tool for identifying clusters. correct answers False The sales of a company (in million dollars) for each year are shown in the table below, identify the linear regression model in the form y=mx+b and report the values of m (slope) and b (intercept) as well as the estimated value of y when the value of x is 10. x (year) 2005 2006 2007 2008 2009 y (sales) 12 19 29 37 45 NOTE: You should consider the value x as the elapsed time. For 2005 this would be 0 years, for 2006 it would be 1 year and for 2012 it would be 7 years. What is the predicted value of y (in millions of dollars) when the year is 2012? correct answers
Which of the following statements will generate a multiple linear regression model within R where the output or predicted variables is Sales and the prediction variables include temperature and unemploymentrate? correct answers lm(sales~temperature+unemploymentrate) True or False: Qualitative variables are often referred to as categorical. correct answers True Which of the following is NOT a classification technique? correct answers Principle components analysis True or False: Bayes theorem classifies cases by calculating the probability that the case belongs to each class and then selecting the one with the highest probability. correct answers True The value of K should typically be an odd number for what reason? correct answers It ensures that when classifying a solution there will not be a tie Assuming K=1 how would the point X be classified using KNN?
d3 1.75 Red d4 4 Blue d5 5 Red d6 6.5 Red correct answers Red Assuming you have the following data values (4,6,9,20,8,7), what is the min-max normalized value for 6. X* = (Xv - min(X)) / (max(X) - min(X) Where X is the set of data values and Xv is the value to score. Provide your response rounded to the thousandths place: correct answers 0. Assuming you have the following data values (3,6,9,14,2), what is the Z-Score normalized value for 5. X* = (Xv - mean(X)) / SD(X) Where X is the set of data values and Xv is the value to score. Provide your response rounded to the thousandths place: correct answers -0. Assume that you are the data scientist for the GreatFoods! Supermarket chain. In an effort to increase sales of locally produced food such as eggs, milk, and bread, your manager asks you to develop a data mining solution that can identify the probability that a customer will purchase eggs when they purchase milk and vice versa. Which technique are you most likely to use? correct answers Bayes Classifier Assuming a data set with 20 training outcomes of which 12 are positive, what is the Entropy? Round your answer to the nearest thousandths place. correct answers 0. Assuming a data set with 1000 training outcomes of which 332 are positive, what is the Entropy? Round your answer to the nearest thousandths place. correct answers 0.
Assuming a data set with 512 training outcomes of which 292 are negatives, what is the Entropy? Round your answer to the nearest thousandths place. correct answers 0. True or False: Information gain is the reduction of entropy. correct answers True True or False: Assuming we have 30,000,000 species and we eliminate one of them we can say that this decision has a large information gain? correct answers False True or False: Entropy is a measure of the uncertainty or variability in a decision or choice within a decision tree. correct answers True True or False: In a biological neuron, signals are received through the axon to the synapses where an activation decision is made. correct answers False True or False: Weights in the artificial neuron are adjusted to ensure that the inputs will produce the output while training. correct answers True The first artificial neural network model was developed by: correct answers McCulloch and Pitts The concept of the perceptron was developed in the 1960's by: correct answers Frank Rosenblatt ______________ wrote a book in 1969 describing the limitations of the perceptron which led to a drop in interest in neural networks for many years. correct answers Minsky and Papert Which of the following is not a category of transfer function in neural networks? correct answers Correlation True or False: An artificial neuron, like a biological neuron can have multiple inputs and multiple outputs. correct answers False
True/False: A regression model has a R^2 statistic of .95. This indicates that the regression model is NOT a good fit and does a poor job of predicting the outcome based upon the input variables. correct answers False True/False: A learning algorithm that is very accurate to the available training data, but when exposed to new cases has a high degree of variance and error is set to be "Overfit". correct answers True Assume that you are the data scientist for a new email provider called fastmail.com. Fastmail intends to differentiate their email service from other email providers by providing excellent spam mail detection and elimination. You have been tasked with developing a machine learning solution that can detect whether an email message received into a users mail inbox is a spam mail. Which of the following techniques are you most likely to use? correct answers A Classifier based upon Bayes theorem Assuming you have the following sample data values (11,5,2,12,9), what is the Z-Score normalized value for 7. Provide your response rounded to the hundredths place. correct answers -
Assuming you have the following data values (12,11,2,13,8,10), what is the min-max normalized value for 6. Provide your response rounded to the thousandths place. correct answers 0. True or False: When training a neural network the goal is to minimize error which is defined as difference between the target output and the actual output. correct answers True True or False: Each training instance of data is presented to the network exactly once during training with the back propagation algorithm which is why a very large amount of training data is required. correct answers False You are training the following perceptron. The neuron in this perceptron has a sigmoid activation function. The sigmoid function is represented by the following equation:
f(x,w) = 1 / (1+e^(w1x1+w2x2)) Using the update function for the weights: wi(t+1) = wi(t)+n(y-f(x,w))f(x,w)(1-f(x,w))xi with a learning rate of η=1, and assuming that the current weights are w1 = 0.2 and w2 = 0.3, compute an iteration of the new weights by computing error and applying back to the inputs. 1 wi 0 w --> 1 Output correct answers New W1 = 0. New W2 = 0. You are training the following perceptron. The neuron in this perceptron has a sigmoid activation function. The sigmoid function is represented by the following equation: f(x,w) = 1 / (1+e^(w1x1+w2x2)) Using the update function for the weights: wi(t+1) = wi(t)+n(y-f(x,w))f(x,w)(1-f(x,w))xi with a learning rate of η=1, and assuming that the current weights are w1 = 0.1 and w2 = 0.1, compute an iteration of the new weights by computing error and applying back to the inputs. .5 wi 1 w --> .5 Output correct answers New W1 = 0. New W2 = 0. You are training the following perceptron. The neuron in this perceptron has a sigmoid activation function. The sigmoid function is represented by the following equation: f(x,w) = 1 / (1+e^(w1x1+w2x2)) Using the update function for the weights: wi(t+1) = wi(t)+n(y-f(x,w))f(x,w)(1-f(x,w))xi
