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前些天发现了一个巨牛的人工智能学习电子书,通俗易懂,风趣幽默,无广告,忍不住分享一下给大家。(点击查看学习资料)
public class LeastSquares {
public static void matching(double[] x, double[] y, double[] input, double fully) {
double k = getK(x, y);
double b = getB(x, y);
System.out.println("线性回归系数 k 值:\t" + k + "\n" + "线性回归系数 b 值:\t" +
b);
double maxy = 0; //用来记录最大偏差
//寻找最大偏差
for (int i = 0; i < input.length; i++) {
if (Math.abs(k * input[i] + b - y[i]) > maxy){
maxy = Math.abs(k * input[i] + b - y[i]);
}
}
System.out.println("最大偏差为:" + maxy);
//求灵敏度
double s = 0;
double sum = 0;
for (int i = 1; i < y.length; i++) {
sum += y[i] - y[i-1];
}
s = sum / (y.length - 1) / 20;
System.out.println("灵敏度为:" + Math.abs(s));
//求非线性误差
System.out.println("非线性误差为:" + Math.abs(maxy/fully*100) + "%");
}
//返回 x 的系数 k 公式:k = (n sum( xy ) - sum( x ) sum( y )) / (n sum( x^2 )-sum(x) ^ 2)
public static double getK(double[] x, double[] y) {
int n = x.length;
return (double) ((n * pSum(x, y) - sum(x) * sum(y)) / (n * sqSum(x) - Math.pow(sum(x),
2)));
}
//返回常量系数系数 b 公式:b = sum( y ) / n - k * sum( x ) / n
public static double getB(double[] x, double[] y) {
int n = x.length;
double k = getK(x, y);
return sum(y) / n - k * sum(x) / n;
}
//求和
private static double sum(double[] ds) {
double s = 0;
for (double d : ds)
{
s = s + d;
}
return s;
}
//求平方和
private static double sqSum(double[] ds) {
double s = 0;
for (double d : ds) {
s = (double) (s + Math.pow(d, 2));
}
return s;
}
//返回对应项相乘后的和
private static double pSum(double[] x, double[] y) {
double s = 0;
for (int i = 0; i < x.length; i++) {
s = s + x[i] * y[i];
}
return s;
}
public static void main(String[] args) {
double[] x1 = {52.5,55,60,65,70,75,80,85,90,95,100};
double[] y1 = {0,-0.54,-1.46,-2.32,-3.20,-4.06,-4.90,-5.72,-6.51,-7.31,-8.01};
double[] inputs1 = x1;
System.out.println("Pt100 热电阻测温实验拟合直线:");
matching(x1, y1,inputs1,y1[y1.length-1]);
}
}
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