Research Article
Credit Risk Prediction Using Fuzzy Immune Learning
Table 2
Parameter specification of IFAIS in our experiments.
| Parameter | Value in Australian | Value in German |
| initial Population Size | 100 | 300 | max Iteration | 50 | 50 | default Age | 5 | 5 | selection Size | 100 | 100 | clone Number | 10 | 10 | max Term Changes Number | 3 | 2 | dontCare Replacement Rate | 0.5 | 0.2 | max Rule Set Size | 5 | 10 | accuracy Threshold | 0.03 | 0.03 | max Rule Similarity Length | 10 | 17 | min Covered Percent | 0 | 30 | memory Weight | 0.5 | 0.5 | | 0.01 | 0.35 | | 0.69 | 0.1 | | 0.01 | 0.45 | | 0.29 | 0.1 | | 0.8 | 0.999 | | 0.2 | 0.001 |
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