[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fkS3nmlA1GzWdD6TwvOswri0GKRkcxzcyfWZgxKcbP2Y":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":12,"question":19,"related":20,"source":24,"type":25},[],"2025-12-01 16:09:35",246901652,[8,9,10,11],"极大似然估计属于贝叶斯主义","极大似然估计需先假设某种概率分布形式","极大似然估计的任务是利用训练集估计参数","极大似然估计做了独立同分布假设",{"count":13,"courseId":14,"courseImg":15,"courseName":16,"workId":17,"workName":18},84,"53e1d2ef4961cca8eea3e23969ad2cb9","https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002F03a579384a6dc297c89809b582fcc767.png","默认课程","exam_168281068","机器学习初步","下列说法错误的是()",[21,26,35,44,53,62,71,80,89,98],{"answer":22,"createTime":5,"id":6,"options":23,"question":19,"source":24,"type":25},[],[8,9,10,11],"v1",0,{"answer":27,"createTime":5,"id":28,"options":29,"question":34,"source":24,"type":25},[],246901653,[30,31,32,33],"指数函数","绝对值函数","对数函数","二次函数","对数线性回归是令广义线性模型中的联系函数为什么函数的特例",{"answer":36,"createTime":5,"id":37,"options":38,"question":43,"source":24,"type":25},[],246901654,[39,40,41,42],"1979","1966","1993","1956","第一篇关于决策树的工作在哪一年发表的",{"answer":45,"createTime":5,"id":46,"options":47,"question":52,"source":24,"type":25},[],246901655,[48,49,50,51],"Gain(D,a)+IV(a)","Gain(D,a)\u002FIV(a)","Gain(D,a)-IV(a)","Gain(D,a)*IV(a)","增益率的表达式是Gain_ratio(D,a)=()",{"answer":54,"createTime":5,"id":55,"options":56,"question":61,"source":24,"type":25},[],246901656,[57,58,59,60],"验证集;需要","验证集;不需要","训练集;不需要","训练集;需要","我们通常将数据集划分为训练集,验证集和测试集进行模型的训练,参数的验证需要在()上进行,参数确定后()重新训练模型",{"answer":63,"createTime":5,"id":64,"options":65,"question":70,"source":24,"type":25},[],246901657,[66,67,68,69],"降低;降低","增加;降低","降低;增加","增加;增加","&quot;一对一&quot;相较于&quot;一对其余&quot;,存储开销(),测试时间开销()",{"answer":72,"createTime":5,"id":73,"options":74,"question":79,"source":24,"type":25},[],246901658,[75,76,77,78],"以很低概率得到很好的模型","以很低概率得到不好的模型","以很高概率得到很好的模型","以很高概率得到不好的模型","以下哪个是对概率近似正确(PAC)的正确解释",{"answer":81,"createTime":5,"id":82,"options":83,"question":88,"source":24,"type":25},[],246901659,[84,85,86,87],"对每个样本 x 选择能使后验概率 P(c∣x) 最大的类别标记","对每个样本 x 选择能使条件风险 R(c_i∣x) 最大的类别标记","对每个样本 x 选择能使条件风险 R(c_i∣x)最小的类别标记","对每个样本 x 选择能使后验概率 P(c∣x) 最小的类别标记","以下哪个选项是对贝叶斯最优分类器的描述",{"answer":90,"createTime":5,"id":91,"options":92,"question":97,"source":24,"type":25},[],246901660,[93,94,95,96],"测试集","训练集","验证集","以上选项都可以","调参以什么集合上的性能作为评价标准",{"answer":99,"createTime":5,"id":100,"options":101,"question":105,"source":24,"type":25},[],246901661,[102,103,104],"层次聚类","密度聚类","原型聚类","k 均值聚类属于下列哪一种聚类算法"]