Decision Trees (DT)是用于分类和回归的非参数监督学习方法. 目标是创建一个模型,通过学习从数据特征推断出的简单决策规则来预测目标变量的值. 例如,在下面的例子中,决策树从数据中学习用一组if-then-else决策规则逼近正弦曲线. 树越深,决策规则越复杂,模型也越复杂. 决策树的优点: 易于理解和解释.树可以被可视化. 需要很少的数据准备.其他技术通常需要数据标准化,需要创建虚拟变量,并删除空白值.但请注意,该模块不支持缺少的值. 使用树(即,预测数据)的成本在用于训练树的数…

信息熵(entropy) 信息熵模型(香农Shannon's Entropy Model) 在一个随机事件中,某个事件发生的不确定度越大,熵也就越大,那我们要搞清楚所需要的信息量越 信息增益(IG,Information Gain):决策树构建中节点的选择靠的是信息增益 表示得知特征A的信息而使得D集合的信息不确定性减少的程度. 选 IG 大的那个feature    …

http://blog.csdn.net/pipisorry/article/details/49445465 海量数据挖掘Mining Massive Datasets(MMDs) -Jure Leskovec courses学习笔记 大规模机器学习之决策树Decision Trees {博客内容:Decision Trees.  This is one of the oldest forms of machine-learning, but there are issues that com…

https://www.quora.com/Why-do-people-use-gradient-boosted-decision-trees-to-do-feature-transform Why is linearity/non-linearity important?Most of our classification models try to find a single line that separates the two sets of point. I say that they…

python机器学习-乳腺癌细胞挖掘(博主亲自录制视频)https://study.163.com/course/introduction.htm?courseId=1005269003&utm_campaign=commission&utm_source=cp-400000000398149&utm_medium=share CatBoost Enables Fast Gradient Boosting on Decision Trees Using GPUs https://d…

This is the 2nd part of the series. Read the first part here: Logistic Regression Vs Decision Trees Vs SVM: Part I In this part we’ll discuss how to choose between Logistic Regression , Decision Trees and Support Vector Machines. The most correct ans…

Classification is one of the major problems that we solve while working on standard business problems across industries. In this article we’ll be discussing the major three of the many techniques used for the same, Logistic Regression, Decision Trees…

一.Table for Content 在之前的文章中我们介绍了Decision Trees Agorithms,然而这个学习算法有一个很大的弊端,就是很容易出现Overfitting,为了解决此问题人们找到了一种方法,就是对Decision Trees 进行 Pruning(剪枝)操作. 为了提高Decision Tree Agorithm的正确率和避免overfitting,人们又尝试了对它进行集成,即使用多棵树决策,然后对于分类问题投票得出最终结果,而对于回归问题则计算平均结果.下面是几条…

一.Decision Trees Agorithms的简介 决策树算法(Decision Trees Agorithms),是如今最流行的机器学习算法之一,它即能做分类又做回归(不像之前介绍的其他学习算法),在本文中,将介绍如何用它来对数据做分类. 本文参照了Madhu Sanjeevi ( Mady )的Decision Trees Algorithms,有能力的读者可去阅读原文. 说明:本文有几处直接引用了原文,并不是不想做翻译,而是感觉翻译过来总感觉不够清晰,而原文却讲的很明白清晰.(个人…

Machine Learning Methods: Decision trees and forests This post contains our crib notes on the basics of decision trees and forests. We first discuss the construction of individual trees, and then introduce random and boosted forests. We also discuss…