Predictive models for hotspots occurrence using decision tree algorithms and logistic regression.
Predictive models for hotspots (active fires) occurrence are essential to develop as one of activities in forest fires prevention in order to minimize damages because of forest fires. This work applied the decision tree algorithms i.e., ID3 and C4.5, as well as logistic regression on spatial data of...
| Main Authors: | Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin |
|---|---|
| Format: | Article |
| Language: | English English |
| Published: |
Asian Network for Scientific Information
2013
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/29146/ http://psasir.upm.edu.my/id/eprint/29146/1/Predictive%20models%20for%20hotspots%20occurrence%20using%20decision%20tree%20algorithms%20and%20logistic%20regression.pdf |
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