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这道题一看就是LIS类型的题目。
而且,更重要的是,题目要求的是结果的个数,而不是所有的结果,这样就能用DP了。如果是后者,则需要用Backtrack回溯法了。
class Solution { public int findLongestChain(int[][] pairs) { Arrays.sort(pairs, (o1, o2) -> { if (o1[0] == o2[0]) { return o1[1] - o2[1]; } return o1[0] - o2[0]; }); int[][] dp = new int[pairs.length + 1][2]; dp[0][0] = Integer.MIN_VALUE; dp[0][1] = Integer.MIN_VALUE; int len = 0; for (int[] pair : pairs) { if (dp[len][1] < pair[0]) { dp[++len][0] = pair[0]; dp[len][1] = pair[1]; } for (int i = len; i > 0; --i) { if (dp[i - 1][1] < pair[0] && dp[i][1] > pair[1]) { dp[i][0] = pair[0]; dp[i][1] = pair[1]; } } } return len; } }
其实更简化点的DP做法是,直接dp[i] = Math.max(dp[i], dp[j] + 1)。因为LIS的做法是为了能够达到O(nlgn)的时间复杂度,但我还没想到...
dp[i] = Math.max(dp[i], dp[j] + 1)
O(nlgn)
另一个做法是贪心。
class Solution { public int findLongestChain(int[][] pairs) { Arrays.sort(pairs, (o1, o2) -> { return o1[1] - o2[1]; }); int len = 1; int[] lastPair = pairs[0]; for (int i = 1; i < pairs.length; ++i) { if (pairs[i][0] > lastPair[1]) { ++len; lastPair = pairs[i]; } } return len; } }
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这道题一看就是LIS类型的题目。
而且,更重要的是,题目要求的是结果的个数,而不是所有的结果,这样就能用DP了。如果是后者,则需要用Backtrack回溯法了。
其实更简化点的DP做法是,直接
dp[i] = Math.max(dp[i], dp[j] + 1)
。因为LIS的做法是为了能够达到O(nlgn)
的时间复杂度,但我还没想到...另一个做法是贪心。
The text was updated successfully, but these errors were encountered: