随机森林:是一个包含多个决策树的分类器, 并且其输出的类别是由个别树输出的类别的众数而定.随机森林对回归的结果在内部是取得平均但是并不是所有的回归都是取的平均,有些是取的和. 随机森林里的随机 极限树/极端随机树里的随机 样本随机 特征随机 参数随机 模型随机(ID3 ,C4.5) 特征随机 参数随机 模型随机(ID3 ,C4.5) 分裂随机  ET或Extra-Trees(Extremely randomized trees,极端随机树)算法与随机森林算法十分相似,都是由许多决策树构成.极限树

sklearn使用技巧 sklearn上面对自己api的解释已经做的淋漓尽致,但对于只需要短时间入手的同学来说,还是比较复杂的,下面将会列举sklearn的使用技巧. 预处理 主要在sklearn.preprcessing包下. 规范化: MinMaxScaler :最大最小值规范化 Normalizer :使每条数据各特征值的和为1 StandardScaler :为使各特征的均值为0,方差为1 编码: LabelEncoder :把字符串类型的数据转化为整型 OneHotEncoder :特

1. Trees Tree is a recursive structure. 1.1 math nodes https://class.coursera.org/principlescomputing-001/wiki/view? page=trees 1.2 CODE无parent域的树 http://www.codeskulptor.org/#poc_tree.py class Tree: """ Recursive definition for trees plus

题解在下已经写过一次了,所以就不再写了,下面只有代码 题解下载(1):http://pan.baidu.com/s/1hsAUjMs 题解下载(2):http://pan.baidu.com/s/1mhC7EYk A 卿学姐与公主 代码 #include <iostream> #include <cstdio> #include <algorithm> #include <cstring> #define MAXN 100000 #define ls (o&

1.集成学习是指对于同一个基础数据集使用不同的机器学习算法进行训练,最后结合不同的算法给出的意见进行决策,这个方法兼顾了许多算法的"意见",比较全面,因此在机器学习领域也使用地非常广泛.生活中其实也普遍存在集成学习的方法,比如买东西找不同的人进行推荐,病情诊断进行多专家会诊等,考虑各方面的意见进行最终的综合的决策,这样得到的结果可能会更加的全面和准确.另外,sklearn中也提供了集成学习的接口voting classifier. sklearn中具体调用集成学习方法的具体代码如下:

集成学习(Ensemble Learning) 集成学习的思想是将若干个学习器(分类器&回归器)组合之后产生一个新学习器.弱分类器(weak learner)指那些分类准确率只稍微好于随机猜测的分类器(errorrate < 0.5): 集成算法的成功在于保证弱分类器的多样性(Diversity).而且集成不稳定的算法也能够得到一个比较明显的性能提升 常见的集成学习思想有: Bagging Boosting Stacking Why need Ensemble Learning? 1. 弱分

http://www.geeksforgeeks.org/connect-nodes-at-same-level-with-o1-extra-space/ recursive: #include <iostream> #include <vector> #include <algorithm> #include <queue> #include <stack> #include <string> #include <fstrea

three version are provided. disjoint set, linked list version with weighted-union heuristic, rooted tree version with rank by union and path compression, and a minor but substantial optimization for path compression version FindSet to avoid redundanc

1064. Complete Binary Search Tree (30) 时间限制 100 ms 内存限制 32000 kB 代码长度限制 16000 B 判题程序 Standard 作者 CHEN, Yue A Binary Search Tree (BST) is recursively defined as a binary tree which has the following properties: The left subtree of a node contains only

E. Minimum spanning tree for each edge   Connected undirected weighted graph without self-loops and multiple edges is given. Graph contains n vertices and m edges. For each edge (u, v) find the minimal possible weight of the spanning tree that contai

The Tree Panel Component is one of the most versatile Components in Ext JS and is an excellent tool for displaying heirarchical data in an application. Tree Panel extends from the same class as Grid Panel, so all of the benefits of Grid Panels - feat

Decision Tree 及实现 标签: 决策树熵信息增益分类有监督 2014-03-17 12:12 15010人阅读 评论(41) 收藏 举报  分类: Data Mining(25)  Python(24)  Machine Learning(46)  版权声明:本文为博主原创文章,未经博主允许不得转载. 本文基于python逐步实现Decision Tree(决策树),分为以下几个步骤: 加载数据集 熵的计算 根据最佳分割feature进行数据分割 根据最大信息增益选择最佳分割feat

http://elinux.org/Device_Tree_Usage Device Tree Usage     Top Device Tree page This page walks through how to write a device tree for a new machine. It is intended to provide an overview of device tree concepts and how they are used to describe a mac

For a Maximum Segment Tree, which each node has an extra value max to store the maximum value in this node's interval. Implement a modify function with three parameterroot, index and value to change the node's value with[start, end] = [index, index] 

Segment Tree Query I For an integer array (index from 0 to n-1, where n is the size of this array), in the corresponding SegmentTree, each node stores an extra attribute max to denote the maximum number in the interval of the array (index from start

For an array, we can build a SegmentTree for it, each node stores an extra attribute count to denote the number of elements in the the array which value is between interval start and end. (The array may not fully filled by elements) Design a query me

For a Maximum Segment Tree, which each node has an extra value max to store the maximum value in this node's interval. Implement a modify function with three parameter root, index and value to change the node's value with [start, end] = [index, index

For an integer array (index from 0 to n-1, where n is the size of this array), in the corresponding SegmentTree, each node stores an extra attribute max to denote the maximum number in the interval of the array (index from start to end). Design a que

这题也是第二次做,本想第一次做时参考的算法会和老师讲的一样,不想老师讲的算法用在这题感觉还不如思雪园友的算法(http://www.cnblogs.com/sixue/archive/2015/04.html)来的简单,不过老师给的思路是一种挺通用的思路,可以用来解决一系列的问题,但我目前看着有点吃力.我坚持认为对全局变量的使用需十分谨慎,能不用就不用,所以为了不出现全局变量,就无辜多了一串参数.实现代码如下,题目在代码下方 #include <stdio.h> #include <st

这题是第二次做了,两次都不是独立完成,不过我发现我第一次参考的程序,也是参考老师(陈越)的范例做出来的.我对老师给的做了小幅修改,因为我不想有全局变量的的存在,所以我多传了三个参数进去.正序遍历每次都是从1到N吗?看题目我认为应该是,结果我错了,我是对比正确的程序一点点修改才发现的,不容易啊.下面是题目及程序 #include <stdio.h> #include <stdlib.h> #include <string.h> typedef struct { int *

完全二叉树 刚开始只发现了中序遍历是从小到大顺序的.一直在找完全二叉树的层结点间规律...放弃了 不曾想,完全二叉树的规律早就知道啊.根结点为i,其左孩子结点2*i, 右孩子结点2*i+1. 结合此两者即可解决问题! A Binary Search Tree (BST) is recursively defined as a binary tree which has the following properties: The left subtree of a node contains on