FINS5548语言编程代写、Python程序编程
FINS3648/FINS5548 Python Assignment
FinTech Use Case
Compare and contrast results from TWO models designed to predict levels of potential sale price
(fair value) of real estate assets in a specific area given predefined asset and environmental
characteristics (modified data is provided).
Specifically, your IoT FinTech team members are interested to see the effect of “size of living
area” variable called “GrLivArea” on the mean asset value variable called “SalePrice”. You are free
to choose any two relevant models (we have covered few ML variations starting from a base
simple OLS). Your task is to critically explain your steps and results and show model coefficients
and model accuracy, for example in mean square error (MSE) and/or R^2.
Model choices
1. Linear Regression
2. RANSAC Regressor
3. LASSO
4. Polynomials
5. Decision Tree
6. Random Forest
Your team members are keen to learn about python and would like to see and read the python
script with simple explanations of your steps. As a result, delivery is in one python.py script
format as <studendtID_Name.py> with ‘’’<text>’’’ explanations of your steps. The aim is to
describe your detailed steps from input variables to model parameters and compare and contrast
final results in a critical, concise and logical way.
Recommended formats
如有需要，请加QQ：99515681 或邮箱：99515681@qq.com 微信：codehelp
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