Please write your final project in the write-up. The write-up consists of the following: Choose a data set from:https://archive.ics.uci.edu/ml/index.php Explain the data set. Why is it...

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Please write your final project in the write-up. The write-up consists of the following:
Choose a data set from:https://archive.ics.uci.edu/ml/index.php

Explain the data set. Why is it interesting/important to analyze? [15 points]How did you obtain the data? How did you clear the data? [5 points]Describe your research objective, i.e., are you predicting? or are you classifying? How you analyze your data? [10 points]How did you select model? [5 points]Why are you using these methods for model selection and why did it pick the model? [5 points]Explain how you analyze it? How well the model is fit to the data? How did you measure the correctness? [10 points]What are the results? Conclusion. [10 points]Discussion: Pros and cons of methods you use. Any assumptions for your model? Is there any limitation? Any improvement you can do? [15 points]Cite all references. [10 points]Attach the code. [10 points]Attach the data [5 points]
Decision trees:https://www.peggykern.org/uploads/5/6/6/7/56678211/edu90790_decision_chart.pdf
Answered Same DaySep 11, 2021

Answer To: Please write your final project in the write-up. The write-up consists of the following: Choose a...

Suraj answered on Sep 12 2021
147 Votes
Classification Modeling Using Decision Tree
Introduction: The dataset is belongs to the heart patie
nts. In this data there are 13 different dependent variables which are different measures related to the heart disease and one independent variable named target. Which tells that a patient with certain values will have a heart attack/disease or not. It is interesting to analyze data because with the use of this model we can make prediction for the future.
The data is downloaded from the internet.
Data clear is the main part in any modeling. First we will check that is there any missing values in the dataset. If there is missing values present in the data than we will fill that missing value with mean/median/mode. If some columns are unnecessary than drop those columns from the dataset and there are more steps for data cleaning.
The heart disease dataset doesn’t contain any missing value and unnecessary columns in...
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