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- Say that you have the following initial settings for binary logistic regression: x = [1, 1, 3] w = [0, -2, 0.75] b = 0.5 2. Given that x's label is 1, what is the value of w_1, w_2, and w_3 at time t + 1 if the learning rate is 1? For this problem, you may ignore the issue of updating the bias term. 3. What is the value of P(y = 1 | x) given your updated weights from the previous question? 4. Given that x's label is 1, what is the value of the bias term at time t + 1 if the learning rate is 1? 5. What is the value of P(y = 1 | x) given both your updated weights and your updated bias term? 6. Given that x's label is 0, what is the value of P(y = 0| x) at time t + 1 if the learning rate is 0.1? Round your answer to the nearest 1000th as a number [0, 1].Please help with artificial intelligence questuon below If given a number of data samples from pairs of values (x, y) namely {(0, 12), (1, 19), (2, 29), (3, 37), (4, 45)} (1) Make a data plot from the given sample where the vertical axis is the y value and the horizontal axis is the x value. (2) Given a simple regression model: y = a x + b where a, b are constant numbers. Use the given data sample and least square method to predict constants a and b from the regression model. (3) Using the predicted regression model in question (2) above, calculate the estimated value of y if the value of x = 7.Consider the following Confusion Matrix: Actual (down) \ Predicted (across) Yes No Totals Yes 20 5 No 10 15 Totals Based on the given time to event data, what is the value of the cumulative distribution function at t=6 if there are 10 right-censored observations?
- Please help with the ai question below, thanks Given a number of data samples (X, Class) in the attached file where each data sample consists of a variable X and a Class whose value is 1 or 2. (1) Using the given sample data, use the Gradient Descent algorithm to predict the logistic regression model (Note: the logistic regression model is NOT a regression model). (2) Using the logistic regression model as a solution to point (1) above, predict the Class of a sample that has a value of X = 5.6Question 91. Consider the following training set of m=4 training examples: x y 0.1 0.6 1 1.5 0 0.5 3 3.5 Consider the linear regression model hθ(x)=θ0+θ1x. What are the values of θ0 and θ1 that you would expect to obtain upon running gradient descent on this model? (Linear regression will be able to fit this data perfectly.)Assume that the entire sample has 8 positive observations and 4 negatives observations. Variable X1: at the left branch has 9 positive observations and 3 negatives observations;at the right branch has 8 positive observations and 8 negatives observations. What is the information gain or reduction in uncertainty of X1 using the Gini index? (round to two decimal spaces)
- This is a theory question with no data, when given a 99% estimated shortfall using Normal, Lognormal and Lognormal Short VaR - which result is most aggressive and what result is most conservative. Why?Suppose that you want to increase all three of the resource availabilities in the product mix model simultaneously by the same percentage. You want this percentage to vary from 225% to 50% in increments of 5%. Modify the spreadsheet model slightly so that this sensitivity analysis can be performed with a one- way SolverTable, using the percentage change as the single input. Keep track of the computers produced in row 21, the hours used in the range B26:B28, and the total profit. Discuss the results.ASSIGNMENT-1QUANTITATIVE METHODS(STAT-201)Student Full Name:Student ID:CRN No.:Note: 1. All the questions are compulsory.2. Due date: Oct. 21, 2016 until 11:59 P.M.3. Points: Section-I 1Ã6=6 Section-II 1Ã6=6 Section-III 6Ã3=18 Total 30Section-I State whether the following statements are True or False. (1Ã6 = 6) 1. Define the problem is the first step in quantitative analysis.a) Trueb) False2. Sensitivity analysis helps us estimate the effect of known and unknown errors in ourmodel.a) Trueb) False3. Minimum EOL will always equal EVwPI.a) Trueb) False4. When using the EOL as a decision criterion, the best decision is the alternative withthe largest EOL value.a) Trueb) False 2 5. The most common quantitative causal model is regression analysis.a) Trueb) False6. Time-series models enable the forecaster to include specific representations ofvarious qualitative and quantitative factors.a) Trueb) FalseSection-IICircle/tick the right answer from the…
- 5.1.3 complete answer and solution onlt no need explanation It is suspected from theoretical considerations that the rate of water flow from a firehouse is proportional to some power of the nozzle pressure. Assume pressure data is more accurate. You are transforming the data. F 96 129 135 145 168 235 p 11 17 20 25 40 55 What is the exponent of the nozzle pressure in the regression model F = apb?It's a Machine Learning question. Suppose we have market basket data consisting of 100 transactions and 20 items. Compute the total number of possible association rules. If the support for item A is 25%, the support for item B is 90% and the support for itemset {A,B} is 20%. Let the support and confidence thresholds be 10% and 60%, respectively. Compute the confidence of the association rule {A} → {B} & {B} → {A}.In the goodness-of-fit measures, interpret the coefficient of determination for Earnings with Model 3 and what the sample variation of earnings explains. Model 1 Model 2 Model 3 Standard error of the estimate Se 6,648.6753 5,430.0734 5,834.7554 Coefficient of determination R2 0.9597 0.3501 0.7005 Adjusted R2 0.6243 0.8442 0.4045 .