备考CFA考试中是有机器学习相关的知识点的。在这个知识点中考生要掌握的知识点也是很多的,那需要考生掌握哪些知识呢?如果你在备考CFA考试跟着融跃小编看看!
在这个机器学习中考生需要掌握样本与误差和三类机器学习两大部分知识的学习,这两部分知识中又包含很多的小知识,一篇文章是讲不完的,这边有CFA备考知识框架,有需要可以在线咨询CFA老师获取相关的资料!跟着小编看看这一章节的知识考试题,看看会不会做!
练习1:Hierarchical clustering is best described as a technique in which:
A. the grouping of observations is unsupervised.
B. features are grouped into a pre-specified number, k, of clusters.
C. observations are classified according to predetermined labels.
解析:选A。B是不正确的,因为它是K均值聚类。C是不正确的,因为它指的是分类,这涉及到监督学习。
练习2:Dimension reduction techniques are best described as a means to reduce a set of features to a manageable size:
A. without regard for the variation in the data.
B. while increasing the variation in the data.
C. while retaining as much of the variation in the data as possible.
解析:选C。降维技术,如PCA,旨在将特征集减少到一个可管理的大小,同时保留尽可能多的数据变化。
CFA知识学习是长期的事情,但是坚持CFA考试是每一位学员应该做到的。通过CFA考试掌握更多的金融知识,让自己变成富有的人。更多CFA备考知识、资料领取及学习答疑的事情,学员可以在线咨询老师。