https://github.com/joknaa/ml_linearregression
This is a program that performs the Linear Regression algorithm On a set of Data, and shows a graph of the Cost function
https://github.com/joknaa/ml_linearregression
linear-regression machine-learning
Last synced: 7 months ago
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This is a program that performs the Linear Regression algorithm On a set of Data, and shows a graph of the Cost function
- Host: GitHub
- URL: https://github.com/joknaa/ml_linearregression
- Owner: Joknaa
- Created: 2021-03-26T17:54:40.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2021-03-29T11:49:54.000Z (over 4 years ago)
- Last Synced: 2025-03-02T01:39:27.019Z (7 months ago)
- Topics: linear-regression, machine-learning
- Language: Java
- Homepage:
- Size: 551 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# ML_LinearRegression
Yoo ! **Oknaa** here
This is a program that applies the Linear Regression algorithm to a DataSet.### => Graphical User Interface
The user interface is as follows; The user can:
- Add a **Dataset** file.
- Specify the algorithm parameters:
----> The initial values of the **Weight** (P1) and the **Biais** (P0). _(Default: (0,0))_
----> The value of the **Learning rate** (Alpha). _(Default: 0.01)_
----> The number of **Iterations**. _(Default: 50)_
_note: If any of the above parameters were left without input, the program will use their default values._
### => DataSet
The user can input any text file contains a DataSet in the following format:
The first column are the input values (X), the second are the output values (Y)
_note: you can find this file (DataSet2.txt) in the Resources folder._
_note: if the user doent specify any file as a dataset, this one will be used._### => Output Graph
The program calculates the cost of each iteration, and then displays it in a graph.
### => Examples:
##### (P0,P1) = (1,1) .. Alpha = 0.05 .. Number of iterations = 10
##### (P0,P1) = (0,0) .. Alpha = 0.01 .. Number of iterations = 50
##### (P0,P1) = (100,100) .. Alpha = 0.07 .. Number of iterations = 50
##### (P0,P1) = (0,0) .. Alpha = 0.15 .. Number of iterations = 50
