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A Data Scientist, you are supposed to build a multivariate 1linear regression (MLR) model that might be used to predict the Stock Price Index (dependent variable) based on two independent variables namely Interest Rate and Unemployment Rate as they are shown in the mlr_dat.csv dataset. Find the intercept b and the coefficient Wi analytically by consulting the aforementioned problem to the textbook AIMA 3rd Edition pp. 718-721. Compare and show side by side to see how close your MLR model prediction with the actual one (ground truth). Learning Outcomes: LO 5: Apply various techniques to an agent when acting under certainty LO 6: Apply various AI algorithms to solve the problems

A Data Scientist, you are supposed to build a multivariate 1linear regression (MLR) model that might be used to predict the Stock Price Index (dependent variable) based on two independent variables namely Interest Rate and Unemployment Rate as they are shown in the mlr_dat.csv dataset. Find the intercept b and the coefficient Wi analytically by consulting the aforementioned problem to the textbook AIMA 3rd Edition pp. 718-721. Compare and show side by side to see how close your MLR model prediction with the actual one (ground truth). Learning Outcomes: LO 5: Apply various techniques to an agent when acting under certainty LO 6: Apply various AI algorithms to solve the problems

Database System Concepts
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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Please answer clearly, don't just answer!!!! I've asked same question to Bartlely 3 times and got an inaccurate solution!!! PLEASE READ
I NEED ANSWER CLEARLY BRIEFLY COMPLETELY AND CLEARLY ACCORDING TO THE PROVISIONS IN THE PICTURE, PLEASE DO NOT GIVE A SOLUTION AS PICTURED BECAUSE IT DOES NOT WORK!!! 

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#Fit the model using x_train and y_train mlr = LinearRegression () mlr.fit (x_train, y_train) #Print the Intercept and Coefficients of the Model created print ("Intercept:",mlr.intercept_) print ("Coefficients:",mlr.coef_) Incorrect solution, please answer dont #Predict Model y_pred = mlr.predict (x_test) y_pred same with this #Compare Prediction and Actual values mlr_diff = pd. DataFrame ( {'Actual value': y_test, 'Predicted value': y_pred}) mlr_diff.head () Code Image: urt pastas as p Stock rket Interest ate's (2.75,...5,2..2 "unempinynt ates (5.3,5.1,.,5.3,5.4,5.4,.5,.1,5.5,54,5.7,5.9,5.0,,6.1.,6.1,4.1.1,5.,.2..3, "stack Inde brice's (4, 4,17,a0, as, 1a, 14, s,10, 67,, as, 1a, es, a,a,1, M,a 2.35,2.25, .,..,5,1.,.5,1.75s,a.7,. ere Un e e 20 63 53 290 34
Transcribed Image Text:#Fit the model using x_train and y_train mlr = LinearRegression () mlr.fit (x_train, y_train) #Print the Intercept and Coefficients of the Model created print ("Intercept:",mlr.intercept_) print ("Coefficients:",mlr.coef_) Incorrect solution, please answer dont #Predict Model y_pred = mlr.predict (x_test) y_pred same with this #Compare Prediction and Actual values mlr_diff = pd. DataFrame ( {'Actual value': y_test, 'Predicted value': y_pred}) mlr_diff.head () Code Image: urt pastas as p Stock rket Interest ate's (2.75,...5,2..2 "unempinynt ates (5.3,5.1,.,5.3,5.4,5.4,.5,.1,5.5,54,5.7,5.9,5.0,,6.1.,6.1,4.1.1,5.,.2..3, "stack Inde brice's (4, 4,17,a0, as, 1a, 14, s,10, 67,, as, 1a, es, a,a,1, M,a 2.35,2.25, .,..,5,1.,.5,1.75s,a.7,. ere Un e e 20 63 53 290 34
A Data Scientist, you are supposed to build a multivariate linear regression (MLR) model that might be used to predict the Stock Price Index (dependent variable) based on two independent variables namely Interest Rate and Unemployment Rate as they are shown in the mlr_dat.csv dataset. Find the intercept b and the coefficient Wi analytically by consulting the aforementioned problem to the textbook AIMA 3rd Edition pp. 718-721. Compare and show side by side to see how close your MLR model prediction with the actual one (ground truth). Learning Outcomes: LO 5: Apply various techniques to an agent when acting under certainty LO 6: Apply various AI algorithms to solve the problems
Transcribed Image Text:A Data Scientist, you are supposed to build a multivariate linear regression (MLR) model that might be used to predict the Stock Price Index (dependent variable) based on two independent variables namely Interest Rate and Unemployment Rate as they are shown in the mlr_dat.csv dataset. Find the intercept b and the coefficient Wi analytically by consulting the aforementioned problem to the textbook AIMA 3rd Edition pp. 718-721. Compare and show side by side to see how close your MLR model prediction with the actual one (ground truth). Learning Outcomes: LO 5: Apply various techniques to an agent when acting under certainty LO 6: Apply various AI algorithms to solve the problems
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