Josephina is a clever girl and addicted to Machine Learning recently. She 
pays much attention to a method called Linear Discriminant Analysis, which 
has many interesting properties. 
In order to test the algorithm's efficiency, she collects many datasets. 
What's more, each data is divided into two parts: training data and test 
data. She gets the parameters of the model on training data and test the 
model on test data. To her surprise, she finds each dataset's test error curve is just a parabolic curve. A parabolic curve corresponds to a quadratic function. In mathematics, a quadratic function is a polynomial function of the form f(x) = ax2 + bx + c. The quadratic will degrade to linear function if a = 0.

It's very easy to calculate the minimal error if there is only one test error curve. However, there are several datasets, which means Josephina will obtain many parabolic curves. Josephina wants to get the tuned parameters that make the best performance on all datasets. So she should take all error curves into account, i.e., she has to deal with many quadric functions and make a new error definition to represent the total error. Now, she focuses on the following new function's minimum which related to multiple quadric functions. The new function F(x) is defined as follows: F(x) = max(Si(x)), i = 1...n. The domain of x is [0, 1000]. Si(x) is a quadric function. Josephina wonders the minimum of F(x). Unfortunately, it's too hard for her to solve this problem. As a super programmer, can you help her?

InputThe input contains multiple test cases. The first line is the number of cases T (T < 100). Each case begins with a number n (n ≤ 10000). Following n lines, each line contains three integers a (0 ≤ a ≤ 100), b (|b| ≤ 5000), c (|c| ≤ 5000), which mean the corresponding coefficients of a quadratic function.OutputFor each test case, output the answer in a line. Round to 4 digits after the decimal point.Sample Input

2
1
2 0 0
2
2 0 0
2 -4 2

Sample Output

0.0000
0.5000 这题给你n个二次函数,求出最大值的最小值。
其实就是n个二次取出每一个点去最大值,然后构成一个新的二次函数。
于是就变成了二次函数求最小值。
裸三分!
#include<cstdio>
#include<cstring>
#include<cmath>
#include<algorithm>
using namespace std;
int a[],b[],c[];
int n;
double f(double x)
{
double ans=a[]*x*x+b[]*x+c[];
for (int i= ;i<n ;i++){
ans=max(ans,a[i]*x*x+b[i]*x+c[i]);
}
return ans;
}
int main() {
int t;
scanf("%d",&t);
while(t--){
scanf("%d",&n);
for(int i= ;i<n ;i++){
scanf("%d%d%d",&a[i],&b[i],&c[i]);
}
double l=,r=,rmid,lmid;
while(r-l>1e-){
rmid=r-(r-l)/;
lmid=l+(r-l)/;
if (f(rmid)>f(lmid)) r=rmid;
else l=lmid;
}
printf("%.4lf\n",f(l));
}
return ;
}

Error Curves HDU - 3714的更多相关文章

  1. LA 5009 (HDU 3714) Error Curves (三分)

    Error Curves Time Limit:3000MS    Memory Limit:0KB    64bit IO Format:%lld & %llu SubmitStatusPr ...

  2. hdu 3714 Error Curves(三分)

    Error Curves Time Limit: 4000/2000 MS (Java/Others)    Memory Limit: 65536/65536 K (Java/Others) Tot ...

  3. HDU 3714/UVA1476 Error Curves

    Error Curves Time Limit: 4000/2000 MS (Java/Others)    Memory Limit: 65536/65536 K (Java/Others)Tota ...

  4. HDU 3714 Error Curves

    Error Curves 思路:这个题的思路和上一个题的思路一样,但是这个题目卡精度,要在计算时,卡到1e-9. #include<cstdio> #include<cstring& ...

  5. 三分 HDOJ 3714 Error Curves

    题目传送门 /* 三分:凹(凸)函数求极值 */ #include <cstdio> #include <algorithm> #include <cstring> ...

  6. Error Curves(2010成都现场赛题)

    F - Error Curves Time Limit:3000MS     Memory Limit:0KB     64bit IO Format:%lld & %llu Descript ...

  7. 【单峰函数,三分搜索算法(Ternary_Search)】UVa 1476 - Error Curves

    Josephina is a clever girl and addicted to Machine Learning recently. She pays much attention to a m ...

  8. UVA 5009 Error Curves

    Problem Description Josephina is a clever girl and addicted to Machine Learning recently. She pays m ...

  9. UVA 1476 - Error Curves(三分法)

    UVA 1476 1476 - Error Curves 题目链接 题意:给几条下凹二次函数曲线.然后问[0,1000]全部位置中,每一个位置的值为曲线中最大值的值,问全部位置的最小值是多少 思路:三 ...

随机推荐

  1. 浅析Xilinx 三速以太网MAC IP核

    之前在使用Altera的三速以太网MAC IP的基础上,完成了UDP协议数据传输.此次为了将设计移植到xilinx FPGA上,需要用到xilinx的三速以太网MAC IP核,当然也可以自己用HDL编 ...

  2. Selenium_WebDriver_定位元素

    版权声明:本文为博主原创文章,转载请注明出处. 定位单个元素 WebDriver提供了八种元素定位方法,Java中定位语句形如:driver.findElement(By.id()): 何为元素定位? ...

  3. EL表达式多条件判断方式

    <td> <c:forEach items="${cityMap}" var="entry"> <hr> <input ...

  4. 损失函数 hinge loss vs softmax loss

    1. 损失函数 损失函数(Loss function)是用来估量你模型的预测值 f(x) 与真实值 Y 的不一致程度,它是一个非负实值函数,通常用 L(Y,f(x)) 来表示. 损失函数越小,模型的鲁 ...

  5. 【Tools】ubuntu无法virtualenv创建python虚拟环境的解决

    刚有人问我Ubuntu python虚拟环境无法创建问题,报错same file error,防止今后遇到忘记,记录下可能的问题. 1.先在windows上试了下: pip install virtu ...

  6. python学习:使用正则收集ip信息

        使用正则表达式收集主机信息        #!/usr/bin/env python   from subprocess import Popen, PIPE import re def ge ...

  7. CentOS7 修改网卡名称为eth0

    前言 无论是RHEL 7.还是CentOS 7都使用了NetworkManager.service来进行网络管理,当然network服务还是可以继续使用的,但也将会是过渡期的残留品了. 除此之外7版本 ...

  8. mysql cp复制和mysqldump备份测试

    本文来自我的github pages博客http://galengao.github.io/ 即www.gaohuirong.cn 备份策略 针对不同的场景下, 我们应该制定不同的备份策略对数据库进行 ...

  9. esxi 改变虚拟机磁盘格式为精简存储

    最近在部署虚拟机,导入几个之前保存的ovf模板,发现存储已经被耗费的差不多了.检查了下磁盘存储格式 存储类型是 后置备延迟置零 占用空间 简单了解下 三种存储类型 1.厚置备延迟置零: 默认的创建格式 ...

  10. pinvoke 数据交互笔记

    intptr to array string string[]  _outputStrArray=null;  int channelCount = 0;///返回数组大小            In ...