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
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
Related questions
Question
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](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F67c7b2bb-ed45-4c8d-8524-f83b8daeeeb4%2F593143a8-6c7e-4f0b-a662-da4097244dbe%2Fjj5gwb_processed.jpeg&w=3840&q=75)
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](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F67c7b2bb-ed45-4c8d-8524-f83b8daeeeb4%2F593143a8-6c7e-4f0b-a662-da4097244dbe%2Frk87ek8_processed.jpeg&w=3840&q=75)
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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