...and bingo!
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@ -164,7 +164,15 @@ class Temperature(object):
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Which leads me to suspect that someone may have overfitted the
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Which leads me to suspect that someone may have overfitted the
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model for either xyz or iijjkk or some other problem, and one
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model for either xyz or iijjkk or some other problem, and one
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improvement there means disaster here.
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improvement there means disaster here.
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Something tells me to invert again to 1-entropy... and bingo!
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iijjll: 59 (avg time 797.4, avg temp 19.8)
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iijjkl: 41 (avg time 696.1, avg temp 28.5)
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Need to play with this more... and WTF is f anyways?
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Need to play with this more... and WTF is f anyways?
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"""
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"""
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@ -176,4 +184,4 @@ class Temperature(object):
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a = math.sqrt(coldness)
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a = math.sqrt(coldness)
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c = (10 - a) / 100
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c = (10 - a) / 100
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f = (c + 1) * value
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f = (c + 1) * value
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return (-f * math.log2(f)) # max(f, 0.0000)
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return (1 - (-f * math.log2(f))) # max(f, 0.0000)
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