c# linear regression given 2 sets of data

问题

I have 2 sets of data - one is an average position and the other a score so for every position, i have the predicted score of an item -

double[] positions = {0.1,0.2,0.3,0.45,0.46,...};
double[] scores = {1,1.2,1.5,2.2,3.4,...};

I need to create a function that predicts the score for average position, so given a new item with position 1.7. I under stand the function should be something like y=a*x + b but how do i get to it?

Any help will be appreciated!

回答1:

Yes, you have to build a linear function

  y = a * x + b

in order to do this you have to compute the sums (x is predictor's values and y - is corresponding results):

 sx  - sum of x's
 sxx - sum of x * x
 sy  - sum of y's
 sxy - sum of x * y

So

 a = (N * sxy - sx * sy) / (N * sxx - sx * sx);
 b = (sy - a * sx) / N;

来源：https://stackoverflow.com/questions/32433070/c-sharp-linear-regression-given-2-sets-of-data