By Jiawei Han, Micheline Kamber
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Extra info for Data Mining: Concepts and Techniques 2nd Ed Solution Manual
Suppose that we have an 8(A) × 8(B) × 8(C) three-dimensional cube, and k = 8. If we follow case 1, then there will be 8 base cells, 1(roll up to all on A)+8+8=17 2-D cells, 1+1+8(roll up to all on two dimensions other than A)=10 1-D cells, and 1 0-D cell. However, if we try case 2, that is building a 2 × 2 × 2 3-dimensional subcube on one “corner” of the full cube and then fill it with 8 tuples, we will get 8 base cells, 4+4+4=12 2-D cells (a roll up in either dimension results in 4 cells), 2+2+2 = 6 1-D cells (likewise), and 1 0-D cell.
B) If each cube cell stores one measure with 4 bytes, what is the total size of the computed cube if the cube is dense? The total size of the computed cube is as follows. 5. EXERCISES • • • • • 45 all: 1 A: 1,000,000; B: 100; C: 1, 000; subtotal: 1,001,100 AB: 100,000,000; BC: 100,000; AC: 1,000,000,000; subtotal: 1,100,100,000 ABC:100,000,000,000 Total: 101,101,101,101 cells × 4 bytes = 404,404,404,404 bytes (c) State the order for computing the chunks in the cube that requires the least amount of space, and compute the total amount of main memory space required for computing the 2-D planes.
An iceberg condition: count(C) ≥ k where k is a positive integer as a parameter. Output i. The set of computed cuboids that satisfy the iceberg condition, in the order of your output generation; ii. , A:155, AB : 120, ABC : 22, ABCD: 4, ABCE : 6, ABD: 36, where the number after “:” represents the number of nonempty cells. ) (b) Based on your implementation, discuss the following: i. What challenging computation problems are encountered as the number of dimensions grows large? ii. How can iceberg cubing solve the problems of part (a) for some data sets (and characterize such data sets)?