方法一:深度优先搜索
class Solution {
int ans = 0;
public int findTargetSumWays(int[] nums, int target) {
dfs(nums, target, 0, 0);
return ans;
}
public void dfs(int[] nums, int target, int i, int sum){
//数组遍历结束
if(i == nums.length){
if(sum == target) ans++;
return;
}
dfs(nums, target, i + 1, sum + nums[i]);
dfs(nums, target, i + 1, sum - nums[i]);
}
}
方法二:动态规划(转化为01背包)
class Solution {
public int findTargetSumWays(int[] nums, int target) {
int sum = 0;
for (int num : nums) {
sum += num;
}
//数组的元素和为sum,假设正子集和为sumP,负子集和为sumN
//如果可以构造一个表达式,则sumP + sumN = target
//而sumP - sumN = sum -->2 * sumP = sum + target
//可以得到:sumP = (sum + target) / 2,sum + target 为偶数
//所以可以转化为01背包问题,求组合成正子集和sumP的方式有多少种
if (sum < target || (sum + target) % 2 == 1) return 0;
int goal = (sum + target) / 2;
int[] dp = new int[goal + 1];
//当没有任何元素可以选取时,元素和只能是 0,对应的方案数是 1
dp[0] = 1;
for (int num : nums) {
for (int j = goal; j >= num; j--) {
dp[j] += dp[j - num];
}
}
return dp[goal];
}
}