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README.md
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@@ -35,11 +35,11 @@ We implemented this assignment using mainly Keras and Sklearn.
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An example for the ‘Adults’ dataset:
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![](https://
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An example for the ‘Bank-full’ dataset:
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![](https://
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**Code Design:**
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@@ -150,11 +150,11 @@ For adults dataset, the results of the model were:
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- MMDNF = Mean minimum euclidean distance for the not fooled samples was 0.422
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- Several samples that “fooled” the detector:
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![](
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- Several samples that “not fooled” the detector:
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![](
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- Plotting the PCA shows that the fooled samples are very similar to the real data and the not fooled samples are less similar.
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An example for the ‘Adults’ dataset:
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![](https://huggingface.co/nevoit//Generative-Adversarial-Network-/blob/master/figures/Aspose.Words.36be2542-1776-4b1c-8010-360ae82480ae.001.png)
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An example for the ‘Bank-full’ dataset:
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![](https://huggingface.co/nevoit/Generative-Adversarial-Network-/blob/master/figures/Aspose.Words.36be2542-1776-4b1c-8010-360ae82480ae.002.png)
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**Code Design:**
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- MMDNF = Mean minimum euclidean distance for the not fooled samples was 0.422
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- Several samples that “fooled” the detector:
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152 |
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153 |
+
![](huggingface.co/nevoit/Generative-Adversarial-Network-/blob/master/figures/Aspose.Words.36be2542-1776-4b1c-8010-360ae82480ae.003.png)
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- Several samples that “not fooled” the detector:
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157 |
+
![](huggingface.co/nevoit/Generative-Adversarial-Network-/blob/master/figures/Aspose.Words.36be2542-1776-4b1c-8010-360ae82480ae.004.png)
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- Plotting the PCA shows that the fooled samples are very similar to the real data and the not fooled samples are less similar.
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160 |
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