Hello, I was looking to switch from the GIS trainer to the QN trainer. From what I understand, both methods just attempt to solve the maxent weight optimization problem. I was expecting the results to be similar.’
Here is my made up training data: OUTCOME features A feature1 B feature1 feature2 Testing data: ? feature1 ? feature2 ? feature1 feature2 results: feature1 GIS: A: 0.951 B:0.049 QN: A: 0.610 B:0.390 feature2 GIS: A: 0.002 B:0.998 QN: A: 0.169 B:0.830 feature1 feature2 GIS: A: 0.039 B:0.961 QN: A: 0.242 B:0.758 Is this the expected result? Should the two training model give such divergent results? I understand the dataset is trivial, but I think these differences are huge. Any advice? Thank you, Daniel Daniel Russ, Ph.D. Staff Scientist, Office of Intramural Research Center for Information Technology National Institutes of Health U.S. Department of Health and Human Services 12 South Drive Bethesda, MD 20892-5624
