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图0-10 叙利亚战争中阿勒颇市的城市破坏情况估计图
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/3_02.jpg?sign=1739283731-6PgkGYTzrQlR07nu7PZyfInBSQfJlPAO-0-94dc795a19019c7341f6622b05935355)
图2-3 聚类示意图
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/4_01.jpg?sign=1739283731-pBnKmOjI5Re9jLhlOeelCid0c9RiO5mC-0-5dadb8ed2fee889807d5b6120162ccbb)
图2-6 学习曲线(横轴为训练样本数,纵轴为准确率)
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/4_02.jpg?sign=1739283731-6dYLSMDIhlADz6Zt6OFvO03KggfDX9cx-0-7c5307015046193108f6d770a9e88f67)
图2-7 学习曲线(横轴为训练样本数,纵轴为相应误差)
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/5_01.jpg?sign=1739283731-QN2kTLg2tPpVfhd9XINCUtKt4HaFN8ZU-0-87802fd1907590554fb48ecdd76bd7b8)
图4-2 K-Means算法流程示意图
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/5_02.jpg?sign=1739283731-s8waA1FoE7KuF46daP5hlgSy1PlBv2NH-0-f8478ac2185a0e29f04bc3114cdb402f)
图4-7 密度聚类的几个概念定义示意图
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/6_01.jpg?sign=1739283731-3ET7ojK9Fr9vAX4y6phYFUMSDdxVzdOC-0-1d47a4c1979ec381dbf96d26795b6f67)
图7-5 卷积方式Padding
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/6_02.jpg?sign=1739283731-W7mROVHxobGNGIwP1mgHSxcZASJjVilz-0-14b1390c4f51ad0684588d84bf8ecca0)
图7-6 池化示意图
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/6_03.jpg?sign=1739283731-BAf2SBTzrCd7eFXG4PUMPVn0pMgfPVda-0-0b10bc2e821bc862111def54a1c4d60f)
图8-18 StackGAN的基本结构
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/7_01.jpg?sign=1739283731-DVSSnLpC4BcZoad8cdmMl1fOMJfxjX2E-0-d7026a5986ad16436625608b1f27d0d7)
图9-5 长连边和短连边
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/7_02.jpg?sign=1739283731-AdWA6WVKSd1MvWPDeuUo0kawW8z0e1Om-0-45edf789c78046360cf5a08dfe567ede)
图9-6 社会联系的强度与用户联系长度的关联
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/8_01.jpg?sign=1739283731-nRadu97XTZEVis2K266e7w4i48smq4ub-0-659eeebcc3bfce96d1dbae76aff2eb0d)
图9-7 新加坡的Twitter网络
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/8_02.jpg?sign=1739283731-ZiREV3QharoIsaKKvyAgEnwWYltfp5aF-0-d8fc738f8d099463ef238fd0ae672e43)
图9-8 不同用户联系长度的关系频率和关系强度随时间的动态变化
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/9_01.jpg?sign=1739283731-KgFhCivPlnxIaUbYB0Mj1YgrvI4XGt9h-0-605483202c1e03900db1232fca2ab248)
图10-3 肥胖在网络中的传播情况
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/9_02.jpg?sign=1739283731-J7Li0dT58C5CIIjRkhDHogFcYOAjxhhL-0-de540c92aeeee9d7796859eba44b4516)
图10-9 计算同质性网络和异质性网络的感知偏差
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/10_01.jpg?sign=1739283731-xnzLNaqGhaoUp3VTHLcTNclUsWz05PzG-0-66db388181a2ae46558c9e6da85902d4)
图11-17 收入变化与教育程度的关系
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/10_02.jpg?sign=1739283731-rD1de90kcc9PclqFkdQDzeXxXcBFXnhM-0-15e3ecbe96d6e4e7092aa91bc216930d)
图11-18 不同教育程度的工资增长分布