Fuzzy Gold
| Author | darek |
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| Description | Gold with blurry reflections. Needs Blender 2.5. |
| Images | Click the images below for bigger versions: |
| Download | Download the Blend File!(37 KB) |
You may use it for any purpose without permission or attribution.
The Gold Fuzzy is a gold-colored Fuzzy that resides in Shhwonk Fortress. It attacks Mario and Goombella for barging into their territory during the events of Paper Mario: The Thousand-Year Door. During battle, the Gold Fuzzy summons a Fuzzy Horde, which can be attacked; however, defeating the Gold Fuzzy drives the Fuzzy Horde away. After the battle the Gold Fuzzy isn't seen again in the game.
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Looks quite unique. Head ups for the share.
I just add it up to my collections.
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When the test and the FGS are statistically dependent errors, test accuracy can be exaggerated. Two methods are proposed to eliminate the first of these errors, exploring the risk of exacerbating the second. Both require a probabilistic (rather than binary) gold standard of the statement (for example, the probability that each case is abnormal). The most promising of them, the "two-truth" method eliminates selectively those cases where the gold is more ambiguous (probability close to 0.5). When the test and diagnostic errors are independent FGS, this approach can eliminate much of the downward bias caused by an error FGS, without significant risk of exaggerating accuracy of the test. When the test and FGS are dependent errors, the resulting upward bias can lead to accuracy of the test to be overstated, in extreme cases, even before compensation "two-truth" approach is used. Keywords: ROC curve, accuracy of diagnostic tests, evaluation of technology
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Fuzzy gold is like Kellog. He says he has a natural color, but its artificial reality. Perhaps this man has drowned in a pool of gold paint frases para orkut
test accuracy can be exaggerated. methods are proposed to eliminate the first of these errors, exploring the risk of exacerbating the second. Both need a probabilistic ( than binary) gold
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This study uses Monte Carlo methods to analyze the consequences of having a criterion standard ("gold standard") that contains some error when analyzing the accuracy of a diagnostic test using ROC curves. Two phenomena emerge: 1) When diagnostic test errors are statistically independent from inaccurate ("fuzzy") gold standard (FGS) errors, estimated test accuracy declines. 2) When the test and the FGS have statistically dependent errors, test accuracy can become overstated. Two methods are proposed to eliminate the first of these errors, exploring the risk of exacerbating the second. Both require a probabilistic (rather than binary) gold-standard statement..
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