机器学习面试算法的相关内容

文章 2024-08-06 来自：开发者社区

【机器学习】面试问答：PCA算法介绍？PCA算法过程？PCA为什么要中心化处理？PCA为什么要做正交变化？PCA与线性判别分析LDA降维的区别？

面试问答：PCA算法介绍？PCA算法过程？PCA为什么要中心化处理？PCA为什么要做正交变化？（1）简单介绍一下PCA 主成分分析(Principal componet analysis,PCA) 是一种无监督学习方法，利用正交变换把线性相关变量表示的观测数据转换为几个由线性无关变量...

文章 2022-02-15 来自：开发者社区

[转载] 机器学习面试之算法思想简单梳理

本文转载自tornadomeet博客,它是一篇非常好的归纳机器学习的文章.内容包括：朴素贝叶斯、决策树、Logistic回归、KNN、SVM、Boosting、LDA、Apriori等,这样一篇优秀的文章不得不让我转载记录.感谢作者~ 原文链接：http://www.cnblogs.com/tornadomeet/...

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更新时间 2024-08-07 15:15:13

本页面内关键词为智能算法引擎基于机器学习所生成，如有任何问题，可在页面下方点击"联系我们"与我们沟通。

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【机器学习】面试问答：PCA算法介绍？PCA算法过程？PCA为什么要中心化处理？PCA为什么要做正交变化？PCA与线性判别分析LDA降维的区别？

[转载] 机器学习面试之算法思想简单梳理

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