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Text: ARTIFICIAL INTELLIGENCE Assume that we want to minimize function f(x) using genetic algorithm. We use a population of 5 chromosomes: x1, x2, x3, x4, and x5. When we compute their fitness value, we get the following table: Chromosome x1 x2 x3 x4 x5 Fitness 5 28 17 13 For the next generation, what is the probability of x1 to be selected as one of the parent chromosomes? 1/45 What is the probability of x2 to be selected as one of the parent chromosomes? 1/45 What is the probability of x3 to be selected as one of the parent chromosomes? 1/45 What is the probability of x4 to be selected as one of the parent chromosomes? 1/45 What is the probability of x5 to be selected as one of the parent chromosomes? 1/45

          Text: ARTIFICIAL INTELLIGENCE
    Assume that we want to minimize function f(x) using genetic algorithm. We use a population of 5 chromosomes: x1, x2, x3, x4, and x5. When we compute their fitness value, we get the following table:
    
    Chromosome   x1   x2   x3   x4   x5
    Fitness      5    28   17   13
    
    For the next generation, what is the probability of x1 to be selected as one of the parent chromosomes?
    1/45
    
    What is the probability of x2 to be selected as one of the parent chromosomes?
    1/45
    
    What is the probability of x3 to be selected as one of the parent chromosomes?
    1/45
    
    What is the probability of x4 to be selected as one of the parent chromosomes?
    1/45
    
    What is the probability of x5 to be selected as one of the parent chromosomes?
    1/45
        
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artificial intelligence assume that we want to minimize function fx using genetic algorithmwe use population of 5 chromosomesx1x2x3x4and x5 when we compute their fitness value we get the fol 75065

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Computer Science and Information Technology
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Trishna Knowledge Systems 2018 Edition
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Text: ARTIFICIAL INTELLIGENCE Assume that we want to minimize function f(x) using genetic algorithm. We use a population of 5 chromosomes: x1, x2, x3, x4, and x5. When we compute their fitness value, we get the following table: Chromosome x1 x2 x3 x4 x5 Fitness 5 28 17 13 For the next generation, what is the probability of x1 to be selected as one of the parent chromosomes? 1/45 What is the probability of x2 to be selected as one of the parent chromosomes? 1/45 What is the probability of x3 to be selected as one of the parent chromosomes? 1/45 What is the probability of x4 to be selected as one of the parent chromosomes? 1/45 What is the probability of x5 to be selected as one of the parent chromosomes? 1/45
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Transcript

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00:01 So for part a here, we have that x, the number of children in the sample who suffer from the condition is going to be distributed effectively as a binomial with 1 ,797 trials, and the probability of, quote, unquote, success, or the probability of kleinfelter syndrome is 0 .0014.
00:23 So for the probability that more than two of the male births have klein -felter syndrome, so probability that x is strictly greater than 2, we can calculate as 1 minus the probability that x is less than or equal to 2.
00:38 So we can do that as 1 minus be.
00:44 Now the probability that x equals 2, we would do as 1 ,797 choose 2, or in my software here, that's binomial 1797 comma 2, times probability of success, 0 .0014 to the power of 2 times probability of failure, 1 minus 0 .0014, to the power of 1797 minus 2.
01:07 And then we would subtract off the same for when we have value of 1.
01:13 So 1797 choose 1, 0 .0014 to the power of 1 times that are, of 1797 minus 1.
01:24 And then lastly, we do, technically it's 1797 choose 0, which is just going to be 1.
01:31 And we have 0 .0014 to the power of 0, which is also just going to be 1.
01:35 And then we have 1 minus 0 .0014 to the bar of 1797.
01:39 So we get that our probability is going to be roughly 0 .460 to 3 decimal places, 0 .4603.
01:48 Then for part b, using the poisson approximation, we have that the lambda for our poisson distribution...
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