Artificial Intelligence Experiment Report

Course Name: Artificial Intelligence class: 13 level meter This experiment Date: May 8

School Number: 130703010050 Name: highlight score:

First, the name of the experiment

Linear Regression Prediction System

Second, the purpose and requirements of the experiment

The basic method of understanding and mastering linear regression prediction can be programmed to implement a simple linear regression prediction system.

1, familiar with Octave programming language;

2, the linear regression prediction function, the cost function design and implementation;

3. Parameter learning using gradient descent algorithm

Third, the experimental tools

Octave notepad++

Iv. Contents and steps of the experiment

1, installation programming tools: Octave,:

2, after installation octave, double-click the corresponding icon to open the desktop: You can use the command line to run the program, the commonly used commands are as follows:

(1) Change the current directory command: CD

(2) Show current path command: pwd

(3) Show when directory command: LS

3, use notepad++ Editor to open the File New key folder-ex1 inside the program.

4, using notepad++ code editing software to edit the existing code to fill, because the octave software does not have editing capabilities. Drag the cost function into and write to the prediction function.

Similarly, you need to fill in the code

5, start octave software. Use the CLC command to clear the screen, and then use the CD command to make changes to the file path, completed after the execution of the EX1 program. The results are as follows:

Initial diagram:

Forecast Trend Chart:

Stereoscopic diagram:

Initial position Map:

Best location Map:

V. Summary of the Experiment

This experiment allows me to understand and master the basic methods of linear regression prediction, which can be programmed to implement a simple linear regression prediction system. Also familiar with the
Octave programming language, the design and implementation of linear regression prediction function and cost function, and the ability to use gradient descent algorithm for parameter learning.

Artificial Intelligence Experiment Report