[SOLVED] Cse343/ece343 assignment-1 linear and logistic regression, ml in practice
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• Your submission should be a single zip file 2020xxx_HW1.zip (Where 2020xxx is your roll number). Include all the files (code and report with theory questions) arranged with proper names. A single .pdf report explaining your codes with results, relevant graphs, visualization and solution to theory questions should be there. The structure of submission should follow:
2020xxx_HW1
|− code_rollno.py/.ipynb
|− report_rollno.pdf
|− (All other files for submission)
• Anything not in the report will not be graded.
• Your code should be neat and well-commented.
• You have to do either Section B or C.
• Section A is mandatory.1. (10 points) Section A (Theoretical)
(e) (1 mark) The parameters to be estimated in the simple linear regression model Y = α+βx+ϵ ϵ N(0,σ) are:
(a) α, β, σ
(b) α, β, ϵ (c) a, b, s
(d) ϵ, 0, σ
(f) (1 mark) In a study of the relationship between X=mean daily temperature for the month and Y=monthly charges on the electric bill, the following data was gathered: X=[20, 30, 50, 60, 80, 90], Y= [125, 110, 95, 90,110, 130]. Which of the following seems the most likely model?
(a) Y= α + βx + ϵ β<0
(b) Y= α + βx + ϵ β>0
(c) Y= α + β1x + β2×2+ϵ β2 < 0
(d) Y= α + β1x + β2×2+ϵ β2 > 0
2. (15 points) Section B (Scratch Implementation)
Logistic Regression
Dataset: Diabetes Healthcare Dataset
Page 2
OR
3. (15 points) Section C (Algorithm implementation using packages)
Implementation of linear regression using libraries:- Split the dataset into 80:20 (train: test)
Dataset: CO2 Emissions Dataset
Page 3