Evaluate the prediction performances of the two models using Accuracy Sensitivity and Hit Rate of class fire for the training and testing sets respectively

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

Question 1

The Canadian Forest Fire Weather Index (FWI) is a meteorologically based index, which has been used worldwide to assist wildfire danger forecasting. It consists of different components that account for the effects of fuel moisture and wind on fire behaviour and spread. The FWI indicator can help shape long-term tourist strategy and to plan future investments under a changing climate. More details about the FWI Components can be found in the given reference. 1

To understand the possible fire danger in a specific area, a dataset Algerian_forest_fires_dataset.csv was provided for analysis. This dataset includes 244 instances that record the daily fire danger condition of two regions of Algeria, namely the Bejaia region located in the northeast and the Sidi Bel-abbes region located in the northwest of Algeria. There are 122 instances for each region, and the time range is from June 2012 to September 2012. The fields include the basic weather condition of the region, also cover the key FWI Components. The daily fire danger records have been classified into “fire” (138) and “not fire” (106) classes.

1. Suppose logistic regression is selected to construct the predictive models in SPSS Modeler, you are to answer the following questions:

(i) Discuss and report the field measurement and role settings.

(ii) Set the ratio of training and testing set as 80% : 20%, construct two (2) logistic regression models using “Enter” method and “Stepwise” method respectively. Evaluate the prediction performances of the two models using Accuracy, Sensitivity, and Hit Rate of class “fire” for the training and testing sets respectively. Report the screenshot of the generated SPSS stream.

2. Compare the two (2) modelling results, answer the following questions:

(i) Report your findings.

(ii) In your opinion, would these two models be valid to assist fire danger forecasting? If so, which model is better? Justify your answer.

[Word limit: 400 words] for the above 2 questions

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