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- Computer Science Suppose that the family is a (d1, d2, p1, p2)-sensitive LSH family. What does this mean specifically with respect to the distance parameters d1 < d2 and the probability parameters p1 > p2? What is the false positive rate and the false positive rate of the family?Given: CFG S->XY | YX X -> Y1 | 1 Y -> 0X | 0 Is the given CFG ambiguous? Prove by getting two (2) parse trees of w = 0000111101 with leftmost derivation. Otherwise, the CFG is not ambiguous.Given: CFG S -> 0S0 | A A -> 1S1 | B B -> 0B0 | 0 Is the given CFG ambiguous? Prove by getting two (2) parse trees of w = 0101100011010 with leftmost derivation. Otherwise, the CFG is not ambiguous.
- What is the computational complexity of a complete jackknife estimate of accuracy and variance for an unpruned nearest-neighbor classifier (Chap.??)? Similarly, what is the computational complexity of an unpruned nearest-neighbor classifier?Consider the problem of searching for genes in DNA sequences using Boyer-Moore algorithm. A DNA sequence is represented by a text on the alphabet {A, C, G, T}, and the gene segment is the pattern. Choose the problem instance for your group. (Choose the text and the pattern for your group.) If you choose a different problem instance, your answer will not be accepted and you will get zero for your solution.Construct the bad-symbol shift (?1) table and the good-suffix shift (?2) table.Which describes the Monge-Elkan similarity measure? A Effective in matching names, since names are often spelled in different ways that sound the same B Retrieves only the strings in \( Y \) whose size makes them match candidates (C) Limits the set of candidate matches by deriving an upper bound on the size of the overlap between a pair c (D) Effective for domains in which more control is needed over the similarity measure
- Based on the cyclomatic complexity measured in previous question, identify the basis set of independent paths.Consider a knowledge base (KB) shown in Figure4. Assume that the initial fact base from a user is {Q /\ N} and the goal state {S}. Based on the initial facts and goal state, show the backward chaining and forward chaining searchpathsMattlan ataach screenshot of graph. Gen ate sets of information (xi, Yi) utilizing = (0 : 0.1 : 2.5)';y=erf(x); in MATLAB. Expect that the result y(t) can be approximated by a 6th - th degree polynomial as far as x(t) (counting a consistent predisposition term, so seven dad rameters altogether): _y(t) = 0₁ + 0₂x(1) + 03x² (1) + 04x³ (1) + 05xª (1) + 0x³ (1) + 07xº (1) Settle for the coefficients 0₁, I = 1,2,3,4,5,6,7 utilizing clump least squares. Com-pare the outcome with the MATLAR capability "polyfit.".
- To what extent does computing a full jackknife estimate of accuracy and variance for an unpruned nearest-neighbor classifier (Chap.??) involve heavy computation?Suppose a Bayesian network has the from of a chain: a sequence of Boolean variables X1, . . . Xn where Parents(Xi) = {Xi−1} for i = 2, . . . , n. What is the complexity of computing P(X1|Xn = true) using enumeration? What is the complexity with variable elimination? Please explain.The set of letters S consists of 30 As, 6 Bs, 24 Cs, 15 Ds, and 15 Es. The set of letters T consists of 25 As, 20 Bs, 15 Cs, 5 Ds and 35 Es. What is the mutual index of coincidence between sets S and T? Leave your answer as a fraction in lowest terms