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Linear Regression is the basic algorithm to get started with machine learning/ deep learning. I had made this for my C mini-project.

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LINEAR-REGRESSION

This project is a machine learning algorithm named linear regression.This algorithm uses C language. This project uses very basic header file with which everybody is familiar. It is a machine learning algorithm therefore inputs(datasets) and outputs (predicted values) has to be provided and it maps the rules(algorithm) for the user. This project is divided into 2 parts using switch case:

  1. Theortical part
  2. Algorithm part

Theortical-Part

It includes the basic knowledge of linear regression and its applications.

Algorithm-Part

It includes the algorthim. This algorithm can find out the relation between two operands.For eg, 1+1=2 ,the algorithm finds out the function of operator + and gives us the solution. (P.S.-It can only find the function/indentity of addition, subtraction and multiplication.)

Understanding the code

The algorithm inputs a dataset, for eg: (1,2),(3,4),(5,6); and returns a line which is suitable for the above dataset in the form of Y= W1x1+W2x2+W3x3. W1,W2,W3 are weights which are randomly initialised. This input is represented in form of a matrix(2-D array). The predicted values are stored in another array. The formula is W1y1+W2y2+W3y3 .In the for loop, first the y^ i.e. is the matrix multiplication ,is calculated. Then with respect to the predicted values, the error is calculated. The formula is (y^-y). The error is multiplied with learning rate. And at last the weights are updated.(W-(error times learning rate)). After a number of iterations, the algorithm is ready. At last, a user defined function is used to mark the accuracy of the algorithm which lies between 0 and 1 .

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Linear Regression is the basic algorithm to get started with machine learning/ deep learning. I had made this for my C mini-project.

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