Question 4
We would now like to test on our testing data that we produced from Question 2. This test will
give the Root Mean Squared Logarithmic Error (RMSLE), which is given by:
=1=1[(1+)(1+)]2RMSLE=1Ni=1N[log(1+pi)log(1+yi)]2
where pi refers to the thith prediction made from X_test, yi refers to the thith value in y_test, and
N is the length of y_test.
Function Specifications:
Should take a trained model and two arrays as input. This will be the X_test and y_test variables
from Question 2.
Should return the Root Mean Squared Logarithmic Error (RMSLE) over the input from the
predicted values of X_test as compared to values of y_test.
The output should be a float rounded to 3 decimal places.
In [78]:
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In [79]:
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Out[79]:
Expected Outputs:.
Question 4We would now like to test on our testing data that we pr.pdf
1. Question 4
We would now like to test on our testing data that we produced from Question 2. This test will
give the Root Mean Squared Logarithmic Error (RMSLE), which is given by:
=1=1[(1+)(1+)]2RMSLE=1Ni=1N[log(1+pi)log(1+yi)]2
where pi refers to the thith prediction made from X_test, yi refers to the thith value in y_test, and
N is the length of y_test.
Function Specifications:
Should take a trained model and two arrays as input. This will be the X_test and y_test variables
from Question 2.
Should return the Root Mean Squared Logarithmic Error (RMSLE) over the input from the
predicted values of X_test as compared to values of y_test.
The output should be a float rounded to 3 decimal places.
In [78]:
1
2
3
4
5
6
In [79]:
1
2
3
4
Out[79]:
Expected Outputs:
![Question 4
We would now like to test on our testing data that we produced from Question 2. This test will
give the Root Mean Squared Logarithmic Error (RMSLE), which is given by:
=1=1[(1+)(1+)]2RMSLE=1Ni=1N[log(1+pi)log(1+yi)]2
where pi refers to the thith prediction made from X_test, yi refers to the thith value in y_test, and
N is the length of y_test.
Function Specifications:
Should take a trained model and two arrays as input. This will be the X_test and y_test variables
from Question 2.
Should return the Root Mean Squared Logarithmic Error (RMSLE) over the input from the
predicted values of X_test as compared to values of y_test.
The output should be a float rounded to 3 decimal places.
In [78]:
1
2
3
4
5
6
In [79]:
1
2
3
4
Out[79]:
Expected Outputs:](https://image.slidesharecdn.com/question4wewouldnowliketotestonourtestingdatathatwepr-230331110202-72253555/85/Question-4We-would-now-like-to-test-on-our-testing-data-that-we-pr-pdf-1-320.jpg)
![Question 4 [15 marks] 4.1 The increased usage of technology makes it.pdf](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)