The table summarizes the variables collected in a study of ICU outcomes. The primary outcome (target) variable is vital status at hospital discharge (STA). Clinicians associated with the study indicate a belief that a key predictor of survival was the patient (AGE). Describe and analyze the parameters of a logistic regression model by completing the following: Explain which characteristic of the STA leads to a consideration of a logistic model as opposed to a linear regression mode. Describe a Python program that can perform the logistic regression model equation of STA on AGE. Describe a Python program of the logit transformation of this logistic regression model.

The table summarizes the variables collected in a study of ICU outcomes. The primary outcome (target) variable is vital status at hospital discharge (STA). Clinicians associated with the study indicate a belief that a key predictor of survival was the patient (AGE). Describe and analyze the parameters of a logistic regression model by completing the following: Explain which characteristic of the STA leads to a consideration of a logistic model as opposed to a linear regression mode. Describe a Python program that can perform the logistic regression model equation of STA on AGE. Describe a Python program of the logit transformation of this logistic regression model.

Similar questions

Develop a simple linear regression model (univariate model) using gradient descent method for experience-salary datasets as it is shown on the following table. Once you got the model, check how close the predicted values against the ground truth and calculate the total error (mean square error) and the accuracy R^2.
The R function for logistic regression is: Question 21 options: logit exp lm glm
why does the linear regression is the best model?
All-subsets regression is superior than stepwise regression in terms of data analysis, therefore explain why this is so.
If you are implementing regularised linear regression and when you tested your hypothesis in a new dataset you found that it suffer from high variance. How can you rectify the model ? Give 3 Solutions
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.
When and why do we use the Proportional, Binomial, and Poisson regression models? How and why do each of these models include degrees of freedom?
When and why do we employ the Binomial, Poisson, and Proportional models of regression?
For classification of cancer or benign tumors, the training set has 1% patients have cancer, when trained logistic regression model, the error found to be 1%. Is the results are excellent or not? Why? Use the editor to format your answer
Modeling and Simulation
Gradient Descent algorithm
Why is RMSE generally the preferred performance measure for regression tasks? A. Because it gives an idea of the average percentage deviation of the predictions from the actual values. B. Because it gives an idea of the average absolute deviation of the predictions from the actual values. C. Because it gives an idea of how much error the system typically makes in its predictions, with a higher weight given to large errors. D. Because it gives an idea of the average deviation of the predictions from the actual values.