MGS 4020 Team Assignment

Classification Modeling

 

 

 

  1. 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:
    1. UCI Machine Learning Repository
    2. Kaggle

 

  1. 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).

 

  1. Build a regression model and interpret.

 

Written Report Guidelines

 

  1. Introduction – what is the goal of the project?

 

  1. Data
    1. Source, variables (put data dictionary in appendix)
    2. Sample Size

 

  1. Methodology
    1. Preliminary Analysis – compute Means and Standard Deviations of each variable in the dataset so you get a sense of what the data look like.
    2. Show pivot table(s) to check relationship of the Xs with the categories of y.
    3. Do a Regression to predict and classify.

 

  1. Results
    1. Write out the model and interpret it.
    2.  Evaluate with R-square and standard error

 

  1. Implementation
    1. Discuss how the model may be used in real life.