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Questions
Q1. Describe the business problem and the potential value of the predictive model to the
client. Propose an analytic solution to the problem and support your
recommendation with references to the conducted data and text analytics.
Q2. Explore the sample data using descriptive statistics, frequency plots and cluster
analysis. Specifically identify any missing, anomalous or inconsistent data
characteristics, explaining the potential impact.
Q3. Describe any treatments or transformations undertaken to resolve, missing,
anomalous or inconsistent data characteristics.
Assignment
Case Study
MIS772 Predictive Analytics Assignment A2
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Q4. Perform text analytics on the “Review” data item, generating at least 5 topic
clusters. Provide a description for each of the clusters generated.
Q5. Develop at least three analytic models to predict whether or not the customers are
likely to recommend the airline services and their perception of value for money,
for each of the following combinations of input characteristics:
a. Using only the structured data (using appropriate columns)
b. Using only the text data (using only the generated text topics and clusters)
c. Using both structured and text data
Q6. For all models provide a summary of the model assessment statistics over the
training and validation data sets.
Q7. Select the best predictive model, possibly an ensemble model, and provide a
summary of the model and its performance.
