6 Considering the log loss equation. Explainhow the logloss is used in logisticregression error function. Show the valueswhen y and y' are 0 or 1 and what theymean in English and what equation sayabout it.AUC-ROC for two models100.8-0.40.2Logistic regression, auc = 0.858SvC, auc = 0.970.00.00.20.40.60.810False Positive RateTrue Positive Rate

The main purpose of any cost function or error function is to quantify the error between…

Answered: Considering the log loss equation.…

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter5: A Survey Of Other Common Functions

Section5.1: Logistic Functions

Problem 32SBE

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World Population The following table shows world population N, in billions, in the given year. Year 1950 1960 1970 1980 1990 2000 2010 N 2.56 3.04 3.71 4.45 5.29 6.09 6.85 a. Use regression to find a logistic model for world population. b. What r value do these data yield for humans on planet Earth? c. According to the logistic model using these data, what is the carrying capacity of planet Earth for humans? d. According to this model, when will world population reach 90 of carrying capacity? Round to the nearest year. Note: This represents a rather naive analysis of world population.
Long-Term Data and the Carrying Capacity This is a continuation of Exercise 13. Ideally, logistic data grow toward the carrying capacity but never go beyond this limiting value. The following table shows additional data on paramecium cells. t 12 13 14 15 16 17 18 19 20 N 610 513 593 557 560 522 565 517 500 a. Add these data to the graph in part b of Exercise 13. b. Comment on the relationship of the data to the carrying capacity. Paramecium Cells The following table is adapted from a paramecium culture experiment conducted by Cause in 1934. The data show the paramecium population N as a function of time t in days. T 2 3 5 6 8 9 10 11 N 14 34 94 189 330 416 507 580 a. Use regression to find a logistic model for this population. b. Make a graph of the model you found in part a. c. According to the model you made in part a, when would the population reach 450?
What situations are best modeled by a logistic equation? Give an example, and state a case for why the example is a good fit.
Logistic Population growth the table and scatter plot give the population of black flies in a closed laboratory container over an 18 day period. (a) Use the logistic command on your calculator to find a logistic model for these data. (b) Use the model to estimate the time when there were 400 flies in the container
Special Rounding Instructions When you perform logistic regression, round the r value to three decimal places and the other parameters to two decimal places. Round all answers to two decimal places unless other-wise indicated. An Epidemic In a city of half a million, there are initially 800 cases of a particularly virulent strain of flu. The Centers for Disease Control and Prevention in Atlanta claims that the cumulative number of infections with this flu strain will increase by 40 per week if there are no limiting factors. Make a logistic model of the potential cumulative number of cases of flu as a function of weeks from initial outbreak, and determine how long it will be before 100, 000 people are infected.
Special Rounding Instructions When you perform logistic regression, round the r value to three decimal places and the other parameters to two decimal places. Round all answers to two decimal places unless other-wise indicated. Fluorescent Bulbs Compact fluorescent light bulbs save energy when compared with traditional incandescent bulbs. Our green energy campaign includes efforts to get local residents to exchange their incandescent bulbs fur fluorescent bulbs. Initially 200 households make the change. Market studies suggest that, in the absence of limiting factors, we could increase that number by 25 each month. In our target area, there are 250,000 households, which we take as the limiting value. Make a logistic model that gives the number of households converting to fluorescent bulbs after t months.
Modeling Human Height with a Logistic Function A male child is 21inches long at birth and grows to an adult height of 73inches. In this exercise, we make a logistic model of his height as a function of age. a. Use the given information to find K and b for the logistic model. b. Suppose he reaches 95 of his adult height at age 16. Use this information and that from part a to find r. Suggestion: You will need to use either the crossing-graphs method or some algebra involving the logarithm. c. Make a logistic model for his height H, in inches, as a function of his age t, in years. d. According to the logistic model, at what age is he growing the fastest? e. Is your answer to part d consistent with your knowledge of how humans grow?
A Population of Foxes A breeding group of foxes is introduced into a protected are and exhibits logistic population growth. After t years, the number of foxes is given by N(t)=37.50.25+0.76t foxes. a. How many foxes were introduced into the protected area? b. Calculate N(5) and explain the meaning of the number you have calculated. c. Explain how the population varies with time. Include in your explanation the average rate of increase over the first 10-year period and the average rate of increase over the second 10-year period. d. Find the carrying capacity for foxes in the protected area. e. As we saw in the discussion of terminal velocity for a skydiver, the question of when the carrying capacity is reached may lead to an involved discussion. We ask the question differently. When is 99 of carrying capacity reached?
Special Rounding Instructions When you perform logistic regression, round the r value to three decimal places and the other parameters to two decimal places. Round all answers to two decimal places unless other-wise indicated. Natural Gas Production The following table shows natural gas production N in trillions of cubic feet in the United states t years after 1940. t=yearssince1940 N=cubicft.intrilliions 0 3.75 10 8.48 20 15.09 30 23.79 40 21.87 50 21.52 60 24.15 a. Make a logistic model for N as a function of t. b. Graph the data and the logistic model. c. Which years production was farthest from the prediction of the logistic model? d. What does the logistic model predict for the amount of natural gas that will be produced in the long run? Note: In other contexts, this would be known as the carrying capacity..

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