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QUESTION 1The method that predicts a value of a given continuous valued variable based on the values of other variables, assuming a linear or nonlinear model of dependency is :a.Cohesionb.Separationc.Regressiond.Correlation5 pointsQUESTION 2Using tables given, calculate following calculate the Cost of each Model. Which one is true? (10 points)a.M2 has higher COSTb.They have the same COSTc.M1 has higher COSTd.We need more information5 pointsQUESTION 3Assume, two attributes have a correlation of 0.02; what does this tell you about the relationship of the two attributes?a.When one decreases the other one increasesb.They have strong correlaionc.They are highly correlatedd.They have weak positive correlation5 pointsQUESTION 4The problem that arises when you fit your model based on your training data is calleda.False Positive (FP)b.False Negative (FN)c.Overfittingd.Underfitting5 pointsQUESTION 5The accuracy of a Classification Model is calculated using: a.Entire Datasetb.None of thesec.Testing setd.Training Set5 pointsQUESTION 6Given two models of similar generalization errors, one should prefer the simpler model over the more complex model, is the definition ofa.Occam’s Razorb.Simple Model Theoryc.Basic Model Principled.Accuracy Models5 pointsQUESTION 7Which one is the most common measure to evaluate K-Means Clustersa.Cohesionb.Separationc.Cluster Meand.SSE5 pointsQUESTION 8The method where you reserve 2/3 for training and 1/3 for testing isa.Cross Validationb.Stratified Trainingc.Bootstrapd.Holdout5 pointsQUESTION 9___________________ measures how closely related are objects in a clustera.Cluster Mean b.Cluster Separationc.Cluster Centroid d.Cluster Cohesion5 pointsQUESTION 10K-means isa.Centroid-based Hierarchical clusteringb.Medoid-based Partitional clustering approachc.Medoid-based Hierarchical clusteringd.Centroid -based Partitional clustering approach5 pointsQUESTION 11For the tree given below:What is the training error (optimistic error) for the parent:a.12/36b.5/36c.10/36d.24/365 pointsQUESTION 12For the tree given below:What is the training error (optimistic error) for the children:a.5/36b.6/36c.24/36d.12/365 pointsQUESTION 13For the tree given below:What is the training pessimistic error for the children (N=0.5):a.8/36b.6/36c.12/36d.26/3610 pointsQUESTION 14K-means is :a.Centroid -based Partitional clustering approachb.Medoid-based Partitional clustering approachc.Medoid-based Hierarchical clusteringd.Centroid-based Hierarchical clustering5 pointsQUESTION 15___________________measures how closely related are objects in a cluster___________________measures how distinct or well-separated a cluster is from other clustersa.Cluster Cohesion – Cluster Separationb.Cluster Separation – Cluster Cohesionc.Cluster Similarity – Cluster Distanced.Cluster Distance – Cluster Similarity5 pointsQUESTION 16Consider the training examples shown in below Table for a binary classification problem (10 points)Calculate the Gini value for the following attributes and answer the following questions:Which attribute is better, Gender, Car Type, or Shirt Size for the 1st split ? a.It does not matter. Algorithm chooses one randomly. b.Shirt Sizec.Genderd.Car Type10 pointsQUESTION 17Consider the training examples shown in below Table for a binary classification problem (10 points)Calculate the Gini value for the following attributes and answer the following questions: Gender, Car Type, Shirt SizeWhat is the right order of the Gini Values from the lowest to highest?a.Gender < Shirt Size < Car Type b.Gender < Car Type < Shirt Sizec.Car Type < Gender < Shirt Size d.Shirt Size < Car Type < Gender
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