[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$ftvSC_F10eE4idlSoemqoDsVXPbFgwZk6Q0uO4szaKxQ":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":10,"question":16,"related":17,"source":27,"type":43},[],"2023-05-07 20:40:38",33448384,[8,9],"对","错",{"courseId":11,"courseImg":12,"courseName":13,"workId":14,"workName":15},"1000009004","https:\u002F\u002Ftihai-oss-cloud.itihey.com\u002Fimg\u002Ff4e4dd841924a91dc656054650011ffd.jpeg","人工智能基础导学","14774743","第六章单元测试","机器学习就是有监督学习",[18,29,38,44,53,62,67,72,75,80],{"answer":19,"createTime":5,"id":20,"options":21,"question":26,"source":27,"type":28},[],33447941,[22,23,24,25],"如果根据一个属性做判断,样本仍然有若干种情况,则该属性不应该出现在决策早期","属性在决策树中的位置不同,决策树的效率是不同的","规则归纳问题,适合用决策树来表示","决策树算法是无监督学习","关于决策树,说法有误的是","v2",0,{"answer":30,"createTime":5,"id":31,"options":32,"question":37,"source":27,"type":28},[],33448107,[33,34,35,36],"0","1","2","3","下列说法中正确的说法个数是( )机器学习的过程中首先需要收集样本数据,并且抽象表现出来.机器学习中的样本数据可以是人工判断的经验条目数据有监督学习中不需要所有训练样本都有明确的&quot;答案&quot;无监督学习和有监督学习需要选取合适的参数来尽可能地靠近目标",{"answer":39,"createTime":5,"id":40,"options":41,"question":42,"source":27,"type":43},[],33448228,[8,9],"聚类算法属于无监督学习",3,{"answer":45,"createTime":5,"id":46,"options":47,"question":52,"source":27,"type":28},[],33448295,[48,49,50,51],"在强化学习中,计算机通过不断与环境交互并通过环境反馈来逐渐适应环境","强化学习的概念是从Alphago战胜李世石之后才提出的","强化学习属于无监督学习的一种,不需要有监督信息","强化学习和有监督学习的过程相似,是&quot;开环&quot;的过程","下列关于强化学习的说法正确的是",{"answer":54,"createTime":5,"id":55,"options":56,"question":61,"source":27,"type":28},[],33448303,[57,58,59,60],"弱监督学习等价于半监督学习","弱监督学习只对部分的样本引入标注知识","半监督学习通过学习有标记的数据,逐渐扩展无标注的数据","迁移学习的核心思想是将利用在任务A上获得的经验去解决相似的任务B","下列关于弱监督学习的说法不正确的是",{"answer":63,"createTime":5,"id":64,"options":65,"question":66,"source":27,"type":43},[],33448379,[8,9],"任务A 与 任务B 具有某种相似性,利用任务A的学习经验,解决任务B,即迁移学习",{"answer":68,"createTime":5,"id":69,"options":70,"question":71,"source":27,"type":43},[],33448380,[8,9],"机器学习分为有监督和无监督等",{"answer":73,"createTime":5,"id":6,"options":74,"question":16,"source":27,"type":43},[],[8,9],{"answer":76,"createTime":5,"id":77,"options":78,"question":79,"source":27,"type":43},[],33448392,[8,9],"有监督学习的最大问题:标注数据稀缺、昂贵",{"answer":81,"createTime":5,"id":82,"options":83,"question":88,"source":27,"type":28},[],33448402,[84,85,86,87],"K近邻算法中K值的选择对分类的结果影响不大","模型测试阶段的测试数据集不能与训练数据集有交集","决策树算法中最能将样本数据显著分开的属性应该在决策早期就使用","支持向量机模型中距离平面最近的几个样本对平面的选择影响最大","下列关于有监督学习的说法不正确的是"]