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oulrich1
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Nov 17, 2025
oulrich1
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- Implemented linear regression test with normalized outputs for sigmoid
- Architecture: 1-8-1 (8 hidden units)
- Training: 50,000 epochs with learning rate 0.1
- Normalizes target outputs to [0,1] range for sigmoid activation
- Achieves MSE of ~0.0017 (well below 0.01 target)
- Tests 11 evenly-spaced points from x=0.0 to x=1.0
- Displays both normalized and denormalized predictions
- Provides regression baseline for network accuracy testing
- Implemented linear regression test with normalized outputs for sigmoid - Architecture: 1-8-1 (8 hidden units) - Training: 50,000 epochs with learning rate 0.1 - Normalizes target outputs to [0,1] range for sigmoid activation - Achieves MSE of ~0.0017 (well below 0.01 target) - Tests 11 evenly-spaced points from x=0.0 to x=1.0 - Displays both normalized and denormalized predictions - Provides regression baseline for network accuracy testing
oulrich1
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claude/improve-toy-examples-019BnKbFALhbwKVRZSos7MpX
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