Question: Consider the following dataset with two quasi-identifiers (age and zip) and one sensitive attribute (disease):...

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Question: Consider the following dataset with two quasi-identifiers (age and zip) and one sensitive attribute (disease): sn --- 1 P600 GAWNH 2 3 4 5 6 7 8 age 9 29 34 40 31 AWAWA W 40 32 41 46 37 10 33 11 47 12 47 zip --- 39056 15010 Part B: [10pts] Repeat part A for k=3. Part C: [10pts] Repeat part A for k=4. 58014 39056 56017 51100 82030 37060 39010 41038 39056 26010 Part A: [10pts] Apply the algorithm for k =2. A. What is the number of the resulting ECs? disease B. Compute the Discernibility Metric (CDM). C. Compute the /Loss/Utility (w.r.t. age). D. Indicate/Compute the distinct and entropy /-diversity. Heart disease Autism Autism Alzheimer Heart disease AIDS Apply the k-anonymization algorithm (greedy partitioning) discussed in class. The partitioning must be done w.r.t the two quasi-identifiers zip and age (in this order). Show all the steps - showing only the final answer will result in zero score. Autism Heart disease Anorexia Anorexia Alzheimer Heart disease Part D: [5pts] Plot CDM and /Loss/Utility VS the different k values (2, 3, and 4). State your observations/findings. Question: Consider the following dataset with two quasi-identifiers (age and zip) and one sensitive attribute (disease): sn --- 1 P600 GAWNH 2 3 4 5 6 7 8 age 9 29 34 40 31 AWAWA W 40 32 41 46 37 10 33 11 47 12 47 zip --- 39056 15010 Part B: [10pts] Repeat part A for k=3. Part C: [10pts] Repeat part A for k=4. 58014 39056 56017 51100 82030 37060 39010 41038 39056 26010 Part A: [10pts] Apply the algorithm for k =2. A. What is the number of the resulting ECs? disease B. Compute the Discernibility Metric (CDM). C. Compute the /Loss/Utility (w.r.t. age). D. Indicate/Compute the distinct and entropy /-diversity. Heart disease Autism Autism Alzheimer Heart disease AIDS Apply the k-anonymization algorithm (greedy partitioning) discussed in class. The partitioning must be done w.r.t the two quasi-identifiers zip and age (in this order). Show all the steps - showing only the final answer will result in zero score. Autism Heart disease Anorexia Anorexia Alzheimer Heart disease Part D: [5pts] Plot CDM and /Loss/Utility VS the different k values (2, 3, and 4). State your observations/findings.

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To implement the kanonymization algorithm greedy partitioning on the given dataset with the quasiidentifiers age and zip we need to follow the specifi... View the full answer