Table 4: Transactions Dataset Transaction dataset showing transaction IDs and itemsets for rule mining. Transaction ID Items Bought 1 {a, b, d, e} 2 {b, c, d} 3 {a, b, d, e} 4 {a, c, d, e} 5 {b, c, d, e} 6 {b, d, e} 7 {c, d} 8 {a, b, c} 9 {a, d, e} 10 {b, d}   Review Table 4: Transactions Dataset. You are asked to use rule mining on the dataset. What is the confidence for the rule {d} → {b}?

Table 2: Second Dataset for X and Y Dataset showing point numbers and X and Y values for K-means clustering. Point X Y 1 1 3 2 2 2 3 6 7 4 2.5 3.5 5 4 2 6 3 5 7 1 1 8 2 2 9 5 6 10 4 4 11 5.5 2.5 Review Table 2: Second Dataset for X and Y. You decide to use the K-means algorithm on the dataset: K is set to 3 and, initially, Point 5 is the first centroid, Point 6 is the second centroid, and Point 7 is the third centroid. Using Euclidean distance measure, what are the clusters after the first iteration?

Table 6: Training Dataset for Car Type Training dataset for predicting car type from work years and college years. Instance Work Years College Years Car Type 1 4 5.5 Hybrid 2 5 3 Sports 3 4 3.5 Luxury 4 3.5 4.5 Family 5 5 4 Hybrid 6 1 4 Sports 7 4 6 Luxury 8 6 4 Family 9 3 3 Hybrid 10 4.5 4 Sports 11 3 2 Luxury 12 4 2 Family Review Table 6: Training Dataset for Car Type. You decide to use the K-Nearest Neighbors (KNN) model on the dataset to predict car type. Your friend worked for 4 years and attended college for 4 years. If K is set to 7 and the model uses Euclidean distance, which car type will be predicted for your friend?

Table 3: Training Dataset for Pet Type Training dataset for predicting pet type from employment, age, debt, and college degree status. Employed Age Debt College Degree Pet Yes 26 Yes No Cat Yes 45 No Yes Dog No 22 Yes Yes Dog No 50 Yes No Cat Yes 24 Yes No Cat No 33 Yes Yes Dog Yes 62 No No Cat Yes 39 Yes No Dog No 25 Yes No Dog Review Table 3: Training Dataset for Pet Type. Assume we want to use a decision tree to predict a person’s pet type. Using misclassification error as the measure of node impurity, which categorical attribute provides the best split?

Table 1: Centroid X and Y Values Dataset showing data points and their X and Y values for K-means centroid initialization. Data X Y x1 1 1 x2 6 6 x3 7 7 x4 3 2 x5 6 8 x6 2 1 x7 2 3 Review Table 1: Centroid X and Y Values. You decided to cluster the table data into two clusters using K-mean clustering. Initially, point x1 is chosen as Centroid1 and point x2 is chosen as Centroid2. Using Euclidean distance measure, what will be the final X and Y values of the Centroids after the first iteration of the K-mean clustering algorithm?

If a patient’s thyroid gland is shown to have diffused enlargement on a nuclear medicine scan, what pathology is likely?

What did Krashen et al. have the participants do?

Which pathology can cause enlarged mediastinal and hilar lymph nodes, congestive heart failure and the splenomegaly seen in this image?

What disease or condition is represented by this image?

Table 7: Dataset for Pet Type Dataset for predicting pet type from age and home value. Instance Age Home Value ($Millions) Pet 1 28 3.6M Cat 2 33 4.1M Cat 3 38 3.7M Cat 4 48 3.9M Cat 5 48 3.5M Dog 6 58 3.7M Dog 7 63 3.1M Dog 8 68 3.6M Dog Review Table 7: Dataset for Pet Type. If you train a Support Vector Machine (SVM) on the dataset to predict pet type, the result will include how many support vectors?