2.) Use the following data to plot a first order and second order model. I have provided code to generate a second order model, repeat this for a first order model, plot both models and the data on a single plot. Comment on which is the better fit based on the plot. X y 5 15 10 22 15 30 20 31 The following code produces a second-order model, enter this code and then repeat this for a first order model with the appropriate changes made, comment on what each line is doing.

2.) Use the following data to plot a first order and second order model. I have provided code to generate a second order model, repeat this for a first order model, plot both models and the data on a single plot. Comment on which is the better fit based on the plot. X y 5 15 10 22 15 30 20 31 The following code produces a second-order model, enter this code and then repeat this for a first order model with the appropriate changes made, comment on what each line is doing.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Q5) Run the code below to check on the model behavior for different polynomials (2,3, 5,10,20). Comment on the generated figure. In [26]: # Hyperparam initialization eta = 0.25 epochs = 500000 # This will take a while but you can set it to 10000. Poly_degree_values = [2, 3, 5, 10, 20] # Initializing plot plt.title( "Regression Lines for Different polynomials") plt.scatter(data.GranulesDiameter, data.Beachslope, label='Traning Data') # iterating over different alpha values (This is going to take a while) for i in Poly_degree_values: polynomial x = GeneratePolynomialFeatures (X, i) thetaInit - np.zeros( (polynomial_x.shape[1],1)) theta, losses = gradientDescent (polynomial_x, Y, thetaInit, eta, epochs) poly = PolynomialFeatures (i) plot SimpleNonlinearRegression line (theta, X, poly) plt.legend(Poly_degree_values) plt.show() Regression Lines for Different polynomials 2 25 10 20 20 15 10 0.2 0.3 0.4 0.5 0.6 0.7 0.8 In [271: # Write your response here
Correct and detailed answer will be Upvoted else downvoted. Thank you! Plagarised answer will be downvoted directly.
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You work for an loan analytics organization have been tasked with writing a program that simulates an analysis of loan applications. Code a modular program that uses parallel arrays to store loan application credit scores (values generated between 300 and 900), score ratings (poor, fair, good, very good, or exceptional based on credit score) and loan status (approved or declined applications based on credit score). The program must do the following: The program must first ask the user for the number of loan applications that will be in the simulation. This must be done by calling the getNumLoanApplications() function (definition below). After the input of the number of accounts, the program must use loops and random numbers to generate the credit score, score rating, and application result for each loan application in parallel arrays. These arrays must not be declared globally (major error). The following arrays must be declared and populated: creditScores[] - an array of type int…
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Please complete the exercise as instructed and do not use global variables. Please follow the guidelines of what the solution cannot use provided in the second picture. Thank you!
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Models are used for a variety of purposes. Sort the models into groups.