<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[Edwards_June的专栏]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/Edwards_June</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; Edwards_June]]></copyright><item><title><![CDATA[ubuntu装cuda出现xserver running问题]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/79067318</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/79067318</guid><author>Edwards_June</author><pubDate>Mon, 15 Jan 2018 18:10:16 +0800</pubDate><description><![CDATA[如题，注销进入tty停止xserver不成功，解决：
禁用自带nouveau驱动：


（1）直接移除这个驱动（备份出来）

$ mv /lib/modules/4.4.0-31-generic/kernel/drivers/gpu/drm/nouveau/nouveau.ko /lib/modules/4.4.0-31-generic/kernel/drivers/gpu/drm/n]]></description><category></category></item><item><title><![CDATA[grub-efi-amd64-signed安装失败]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/75507822</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/75507822</guid><author>Edwards_June</author><pubDate>Thu, 20 Jul 2017 12:38:51 +0800</pubDate><description><![CDATA[uefi 下grub-efi-amd64-signed 安装失败 




解决方案：新建efi分区即可
https://help.ubuntu.com/community/UEFI#Creating_an_EFI_System_Partition]]></description><category></category></item><item><title><![CDATA[pandas get_dummies()使用]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/73716580</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/73716580</guid><author>Edwards_June</author><pubDate>Sun, 25 Jun 2017 14:20:48 +0800</pubDate><description><![CDATA[In [72]: df = pd.DataFrame({'key': ['b', 'b', 'a', 'c', 'a', 'b'],
   ....:                    'data1': range(6)})

In [73]: pd.get_dummies(df['key'])
Out[73]: 
   a  b  c
0  0  1  0
1  0  1  0
2  1  ]]></description><category></category></item><item><title><![CDATA[决策树实现]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/73008649</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/73008649</guid><author>Edwards_June</author><pubDate>Sat, 10 Jun 2017 22:14:17 +0800</pubDate><description><![CDATA[from  math import log
import operator

# 计算数据集的熵
def calsShannonEnt(dataSet):
    numEntries = len(dataSet)
    labelCounts = {}
    for featVec in dataSet:
        currentLabel = featVec[-1]
        ]]></description><category></category></item><item><title><![CDATA[KNN实现]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/73008593</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/73008593</guid><author>Edwards_June</author><pubDate>Sat, 10 Jun 2017 22:08:14 +0800</pubDate><description><![CDATA[from array import array
from os import listdir
from numpy import *
import operator


def createDataSet():
        group = array([[1.0,1.1],[1.0,1.0],[0,0],[0,0.1]])
        labels = ['A','A',']]></description><category></category></item><item><title><![CDATA[ML逻辑回归实现]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/72812080</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/72812080</guid><author>Edwards_June</author><pubDate>Sat, 10 Jun 2017 22:06:13 +0800</pubDate><description><![CDATA[代码链接：


from numpy import *


def loadDataSet():
    dataMat = []
    labelMat = []
    fr = open('testSet.txt')
    for line in fr.readlines():
        lineArr = line.strip().split()
        dataM]]></description><category></category></item><item><title><![CDATA[机器学习Kmeans实现]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/72812095</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/72812095</guid><author>Edwards_June</author><pubDate>Sat, 10 Jun 2017 22:05:50 +0800</pubDate><description><![CDATA[代码链接：
 
from numpy import *


def loadDataSet(fileName):
    dataMat = []
    fr = open(fileName)
    m = len(fr.readline().split('\t'))
    for line in fr.readlines():
        curLine = line.strip(]]></description><category></category></item><item><title><![CDATA[机器学习PCA实现]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/72812136</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/72812136</guid><author>Edwards_June</author><pubDate>Tue, 30 May 2017 22:03:47 +0800</pubDate><description><![CDATA[代码链接：


from numpy import *


def loadDataSet(fileName, delim='\t'):
    fr = open(fileName)
    stringArr = [line.strip().split(delim) for line in fr.readlines()]
    datArr = []
    for line in s]]></description><category></category></item><item><title><![CDATA[机器学习线性回归实现]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/72812112</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/72812112</guid><author>Edwards_June</author><pubDate>Tue, 30 May 2017 22:02:15 +0800</pubDate><description><![CDATA[代码链接：


from numpy import *


def loadDataSet(fileName):
    numFeat = len(open(fileName).readline().split('\t')) - 1
    dataMat = []
    labelMat = []
    fr = open(fileName)
    for line in fr.r]]></description><category></category></item><item><title><![CDATA[基于SVM手写数字识别]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/72812071</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/72812071</guid><author>Edwards_June</author><pubDate>Tue, 30 May 2017 21:54:25 +0800</pubDate><description><![CDATA[代码链接：http://download.youkuaiyun.com/detail/edwards_june/9856050


from numpy import *


def loadDataSet(fileName):
    dataMat = []
    labelMat = []
    fr = open(fileName)
    for line in fr.readlines(]]></description><category></category></item><item><title><![CDATA[机器学习实现bayes]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/72812055</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/72812055</guid><author>Edwards_June</author><pubDate>Tue, 30 May 2017 21:52:03 +0800</pubDate><description><![CDATA[代码链接：http://download.youkuaiyun.com/detail/edwards_june/9856048


from numpy import *


# 词表到向量的转换函数
def loadDataSet():
    postingList = [['my', 'dog', 'has', 'flea', 'problems', 'help', 'please'],
    ]]></description><category></category></item><item><title><![CDATA[机器学习adaboost实现]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/72811907</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/72811907</guid><author>Edwards_June</author><pubDate>Tue, 30 May 2017 21:29:57 +0800</pubDate><description><![CDATA[学习《机器学习实战》一书时写的代码：
from numpy import *




def loadSimpData():
    datMat = matrix([[1., 2.1],
                     [2., 1.1],
                     [1.3, 1.],
                     [1., 1.],]]></description><category></category></item><item><title><![CDATA[opencv3：AttributeError: 'module' object has no attribute 'CV_LOAD_IMAGE_COLOR']]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/71235475</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/71235475</guid><author>Edwards_June</author><pubDate>Fri, 05 May 2017 19:26:23 +0800</pubDate><description><![CDATA[如题，AttributeError: 'module' object has no attribute 'CV_LOAD_IMAGE_COLOR'
原因版本问题，opencv3使用
IMREAD_COLOR
 代替'CV_LOAD_IMAGE_COLOR']]></description><category></category></item><item><title><![CDATA[Tensorflow CIFAR-10训练例子报错解决]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/65652385</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/65652385</guid><author>Edwards_June</author><pubDate>Fri, 24 Mar 2017 21:25:28 +0800</pubDate><description><![CDATA[大部分是Api版本问题：


AttributeError: 'module' object has no attribute 'SummaryWriter'
tf.train.SummaryWriter改为：tf.summary.FileWriter


AttributeError: 'module' object has no attribute 'summaries']]></description><category></category></item><item><title><![CDATA[使用Apriori进行关联分析]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/56014491</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/56014491</guid><author>Edwards_June</author><pubDate>Mon, 20 Feb 2017 15:42:56 +0800</pubDate><description><![CDATA[源码有问题,贴出修改后可运行代码：def loadDataSet():
    return [[1, 3, 4], [2, 3, 5], [1, 2, 3, 5], [2, 5]]


def createC1(dataSet):
    C1 = []
    for transaction in dataSet:
        for item in transaction:
      ]]></description><category></category></item><item><title><![CDATA[心路历程]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/54428571</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/54428571</guid><author>Edwards_June</author><pubDate>Mon, 16 Jan 2017 11:28:49 +0800</pubDate><description><![CDATA[2017.1.14
这几天总结了研一上半年所做的事，把这学期刷过算法题大部分都blog了，开学时定下的小目标也完成了。接下来，开始深度学习的旅程。]]></description><category></category></item><item><title><![CDATA[木块砌墙]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/54428553</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/54428553</guid><author>Edwards_June</author><pubDate>Mon, 16 Jan 2017 11:28:12 +0800</pubDate><description><![CDATA[用 1×1×1, 1×2×1以及2×1×1的三种木块（横绿竖蓝，且绿蓝长度均为2），

搭建高长宽分别为K × 2^N × 1的墙，不能翻转、旋转（其中，0

有多少种方案，输出结果
对1000000007取模。
举个例子如给定高度和长度：N=1 K=2，则答案是7，即有7种搭法。


#ifdef WIN32
#define ll __int64
#else
#define l]]></description><category></category></item><item><title><![CDATA[最长公共子序列]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/54428529</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/54428529</guid><author>Edwards_June</author><pubDate>Mon, 16 Jan 2017 11:27:42 +0800</pubDate><description><![CDATA[什么是最长公共子序列呢?好比一个数列 S，如果分别是两个或多个已知数列的子序列，且是所有符合此条件序列中最长的，则S 称为已知序列的最长公共子序列。
举个例子，如：有两条随机序列，如 1 3 4 5 5 ，and 2 4 5 5 7 6，则它们的最长公共子序列便是：4 5 5。
提示：最容易想到的算法是穷举搜索法，但考虑到最长公共子序列问题也有最优子结构性质，可以用动态规划解决。
#defi]]></description><category></category></item><item><title><![CDATA[交替字符串]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/54428496</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/54428496</guid><author>Edwards_June</author><pubDate>Mon, 16 Jan 2017 11:26:57 +0800</pubDate><description><![CDATA[输入三个字符串s1、s2和s3，判断第三个字符串s3是否由前两个字符串s1和s2交错而成，即不改变s1和s2中各个字符原有的相对顺序，例如当s1 = “aabcc”，s2 = “dbbca”，s3 = “aadbbcbcac”时，则输出true，但如果s3=“accabdbbca”，则输出false。
#define N 100

bool isInterLeave(string a, stri]]></description><category></category></item><item><title><![CDATA[格子取数3]]></title><link>https://blog.youkuaiyun.com/Edwards_June/article/details/54428483</link><guid>https://blog.youkuaiyun.com/Edwards_June/article/details/54428483</guid><author>Edwards_June</author><pubDate>Mon, 16 Jan 2017 11:26:33 +0800</pubDate><description><![CDATA[给定m*n的矩阵，每个位置是一个整数，从左上角开始，每次只能朝右、上和下走，并且不允许两次进入同一个格子，走到右上角，最小和。
#include 
using namespace std;

#define M 4
#define N 4

int dp[M][N];

void initDp() {
	for (int i = 0; i < M; ++i) {
		for (int j = 0]]></description><category></category></item></channel></rss>