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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=1738902970-WTc2TYVzPIFgLvZl7JaILZqb6TsLzIrB-0-244b63a176ce30f6a4f78dbe12416814)
图2-3 聚类示意图
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/4_01.jpg?sign=1738902970-hkRSG3WntjIwGCPO93JDasTu6iZO7yTx-0-95aba27cb1946ef7150edcc6a7605f73)
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=1738902970-wlKyJ4crscclDokGNBfpxaBIco69osvm-0-18c0fad8a7ff2bec84bee8c7fe604f04)
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=1738902970-6Whtik7Jrzy57pI2JtHGToOOFg7pxywp-0-76244fac1be2202aa5ccda304cfef304)
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=1738902970-om0xm76q3P5trfL8JtEsRHprYVwJ34l3-0-16ba3effbc0e5b397053a6c5ee18b6ff)
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=1738902970-06pho1OSYgUi4yMW3nklHo1Ea0q2cLUz-0-e5a3b99da6ce541df0853f04a646335c)
图7-5 卷积方式Padding
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/6_02.jpg?sign=1738902970-JTxUYTQz4tWoAXCXElDnj0HBlNOJNm6L-0-7e232c04e40322ec1046cbc68b364366)
图7-6 池化示意图
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/6_03.jpg?sign=1738902970-BiAabIbfgzToWsOvTxgFYqYjvgJhdpa5-0-0bcd369fead5a41c7e4cc24b909cd524)
图8-18 StackGAN的基本结构
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/7_01.jpg?sign=1738902970-sKiNOC8XldDNPsN8VIiGWmJ2tAiRHU85-0-237a746860c902b36e300f9f81c04e41)
图9-5 长连边和短连边
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/7_02.jpg?sign=1738902970-nFI6A6fixQISzmcGlBjMDtRM94gh6cF8-0-882d2543da39545ea017618e2ea2ce2b)
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=1738902970-wFSHHy1DTlZCyIKsUt1XxszZK0MRG94F-0-aa65a4fcfb2a9507473f2e7327ef8e54)
图9-7 新加坡的Twitter网络
![](https://epubservercos.yuewen.com/BB22A3/29497588903344006/epubprivate/OEBPS/Images/8_02.jpg?sign=1738902970-O1HdH2UZ0S3MH226Me6eg4jEbZknmDe3-0-cf92f77c2b81529a6d21fb4a5e660456)
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=1738902970-iginYsjDS8PSnbkysV1IM9Zfi18Hruto-0-8043fabc3a9347c1a423d841c874d8b3)
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=1738902970-aRjcKpoABE6Rg2REd2N2q5mOvG9RdmvL-0-331ca479045507f5d1f7604bab1cf1eb)
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=1738902970-yfPNAQoZwLxlOQ3dtlp7D0Cb0XaKYtEB-0-3d745cd273861609e21e72019cf27c3c)
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=1738902970-LMW4n5ma8KYvLIcmo7txOpScZrTW6c2E-0-463320d3c0fe85e61ccaabd12c9af660)
图11-18 不同教育程度的工资增长分布