| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2013: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2012: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2011: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Research Abstract |
Balanced ensemble learning method has been implemented from negative correlation learning. Balanced ensemble learning is able to create weak learning models by changing the learning error functions with the shifted target values. Such learning functions cannot only help in controlling the complexity of the neural network ensembles, but also improve the accuracy of classifications of the learning models.
In comparison, negative correlation learning is able to generate strong learning models. An novel transition learning method between balanced ensemble learning and negative correlation learning has been proposed. The complexity of the learning models could be controlled during the transition period in the learning process.
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