MGS 4020 Team Assignment
Classification Modeling
- Think of something that
you may want to predict in your business (the business of one of the group
members). If you can find data for that variable and potential predictor
variables, that is ideal. If not, use a dataset available online. A couple
of sources are:
- UCI Machine Learning
Repository
- Kaggle
- Find a suitable Numeric dependent variable to
predict from the dataset you pick
Remember that you can have independent variables that are of the
multi-category type – you simply have to make as
many dummy variables as needed (the number of categories minus 1).
- Build a regression model
and interpret.
Written Report
Guidelines
- Introduction
– what is the goal of the project?
- Data
- Source,
variables (put data dictionary in appendix)
- Sample
Size
- Methodology
- Preliminary
Analysis – compute Means and Standard Deviations of each variable in the
dataset so you get a sense of what the data look like.
- Show
pivot table(s) to check relationship of the Xs
with the categories of y.
- Do a
Regression to predict and classify.
- Results
- Write
out the model and interpret it.
- Evaluate with R-square and standard
error
- Implementation
- Discuss
how the model may be used in real life.