Title:
Given two words word1 and word2, find the minimum number of steps required to convert word1 to word2. (each operation is counted as 1 step.)
You have the following 3 operations permitted on a word:
a) Insert a character
b) Delete a character
c) Replace a character
这题仍可以使用动态规划,问题是,如何得到转移方程。
if a[i] == b[j] then d[i,j] = d[i-1,j-1]
但是不相等的情况下如何计算呢
题目给出了三种可能方式,结果就是根据这三种方式进行
if a[i] != b[j] then min(
a[i-1,j]//相当于删除a[i-1]
a[i,j-1]//相当于插入a的末尾,插入的为b的末尾,这样a,b的末尾相等,所以,要同时减1
a[i-1,j-1]//相当于替换
)
https://blog.csdn.net/zxzxzx0119/article/details/82054807
int minDistance(string word1,string word2){ int m = word1.size(); int n = word2.size(); vector<vector<int> > result(m+1,vector<int>(n+1)); for (int i = 0 ; i <= m ; i++) result[i][0] = i; for (int j = 0 ; j <= n ; j++) result[0][j] = j; for (int i = 0; i < m; i++){ for (int j = 0 ; j < n ; j++){ if (word1[i] == word2[j]) result[i+1][j+1] = result[i][j]; else result[i+1][j+1] = min(result[i][j+1],min(result[i+1][j],result[i][j]) )+1; } } return result[m][n]; }
其他相关问题:
(1)
最长公共字串(连续)
string a= "abcdef";
string b = "abdef";
可以使用动态规划来解决,使用一个二维数组,状态d[i,j]表示到a[i]和b[j]的最长公共字串,这样问题就是要找出状态转移方程。
如果a[i] = b[j] 那么,d[i,j] = d[i-1,j-1]+1
如果a[i] != b[j] 那么 ,d[i,j] = 0
最后再遍历一下数组,来找出最大的字串。
优化,首先,遍历找出最大字串这一步可以放到计算过程中。
string LCS(string s1, string s2){ int len1 = s1.length(); int len2 = s2.length(); int maxLength = 0; int index = 0; int table[1005][1005]; for (int i = 1 ; i < len1+1 ; i++) table[i][0] = 0; for (int i = 1 ; i < len2+1 ; i++) table[0][i] = 0; for (int i = 1 ; i <= len1 ; i++){ for (int j = 1 ; j <= len2 ; j++){ if (s1[i-1] == s2[j-1]){ table[i][j] = table[i-1][j-1] + 1; }else{ table[i][j] = 0; //table[i][j] = (table[i-1][j] > table[i][j-1]) ? table[i-1][j] : table[i][j-1]; } if (table[i][j] > maxLength ){ maxLength = table[i][j]; index = i; } } } return s1.substr(index-maxLength,maxLength); }
例外,一般的动态规划的计算空间都可以降低。将二维空间降至一维空间。
降维对于j一般是正序和逆序,关键是看,如果在计算过程中j-1会被提前计算,则要以相反的顺序进行。比如上面,状态转移是
table[i][j] = table[i-1][j-1] + 1;
如果j是从0 到 len2进行,那么table[j-1]就会被先计算,可是从状态转移我们知道,应该在计算table[j]时,这一行的table[j-1]仍是上一行的,所以应该倒过来进行。
string LCS_continue(string s1,string s2){ int len1 = s1.size(); int len2 = s2.size(); vector<int> result(len2+1); int longest = 0; int index = 0; for (int i = 0 ; i < len2+1; i++) result[i] = 0; for (int i = 0 ; i < len1; i++){ for (int j = len2-1 ; j >=0; j--){ if (s1[i] == s2[j]){ cout<<i<<" "<<j<<endl; result[j+1] = result[j]+1; }else{ result[j+1] = 0; } if (result[j+1] > longest){ longest = result[j+1]; index = j+1; } } } return s2.substr(index-longest,longest); }
(2)公共最长子序列(非连续)
非连续的状态转移也很容易得到。
d[i,j] = d[i-1,j-1]+1 (a[i] == b[j])
d[i,j] = max(d[i-1,j],d[i,j-1]) (a[i] != b[j])
同样,在降维的时候,j仍是要逆序进行。
int LCS_not_continue(string s1,string s2){ int len1 = s1.size(); int len2 = s2.size(); vector<int> result(len2+1); for (int i = 0 ; i < len2+1; i++) result[i] = 0; for (int i = 0 ; i < len1; i++){ for(int j = len2-1 ; j >= 0; j--){ if (s1[i] == s2[j]){ result[j+1] = result[j]+1; }else{ result[j+1] = max(result[j],result[j+1]); } } } return result[len2]; }
(3)最长上升子序列
对于一个序列如1,-1,2,-3,4,-5,6,-7,其最长第增子序列为1,2,4,6
定义递推关系:
dp[i]: 以a_i 为末尾的最长上升子序列的长度
dp[i] = max(1,dp[j]+1) (j < i && a[j] < a[i])
#include <iostream> #include <vector> using namespace std; class Solution{ public: int LIS(vector<int> nums){ vector<int> v(nums.size()+1,1); v[0] = 0; int result = INT_MIN; for (int i = 0; i < nums.size(); i++){ for (int j = 0; j < i; j++){ if (nums[j] < nums[i]) v[i+1] = max(v[i+1],v[j+1]+1); } /*for (int j = 0; j < i+1; j++){ if (j-1 >= 0 && nums[j-1] < nums[i]) v[i+1] = max(v[i+1],v[j]+1); }*/ result = max(result,v[i+1]); } return result; } }; int main(){ int a[] = {4,2,3,1,5}; int size = sizeof(a)/sizeof(int); vector<int> nums(a,a+size); Solution solution; cout<<solution.LIS(nums); system("pause"); }