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日期:2020-05-16 11:09

GUIDELINES FOR THE PROJECT IN BIG DATA FOR BUSINESS

Firstly, note that this project is optional. For the final exam part (60%), you may choose

between taking the final exam (on May 27th at 18:00) or developing a project based on a real

database (deadline May 27th).

? The project should be based on a real data base.

? The final objective is to fit adequate models (studied in this course) to make inference

and predictions that can be of interest of potential users, clients or society.

? Projects should be done individually; however, you may share the same data set with

some colleagues and compare results.

? The length of the project should be smaller than 12 pages; however, you may include

additional plots, the code and any other information of interest in a number of

appendices.

? Project should be based whether on a regression problem (when the output is a

continuous variable) or a classification problem (when the output is a categorical

variable).

The structure of the project should be as following:

1. Introduction

Explain briefly the motivation of the project, the data source and main objectives.

2. Description of variables

Describe clearly each one of the observed variables. Indicate which one is the output

variable and which ones are the input variables (predictors). Indicate clearly if your

project will be based on a regression or a classification problem

3. Descriptive analysis

Show and describe some plots (histograms, boxplots, scatterplots) and data

summaries where you explain the main features of the observed variables.

4. Results using models of type I.

Explain clearly which type of models are going to be used in this section (linear,

logistic, knn, ridge, trees, etc), describe clearly how are they applied, show the main

results in tables and plots and finally, extract the main conclusions from the applied

approach. Comment on the benefits and limitations of the considered type of models.

5. Results using models of type II

Explain clearly which type of models are going to be used in this section (linear

models, knn, trees, etc), describe clearly how are they applied, show the main results

in tables and plots and finally, extract the main conclusions from the applied approach.

Comment on the benefits and limitations of the applied type of models.

6. …

7. Conclusions and extensions

Summarize the main conclusions obtained from the different techniques that have

been considered in your project. Comment on some possible extensions.

8. References

9. Appendix I

10. Appendix II

11. …


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