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https://github.com/lovesaroha/regression-with-single-parameter
In statistics, simple linear regression is a linear regression model with a single explanatory variable.That is, it concerns two-dimensional sample points with one independent variable and one dependent variable (conventionally, the x and y coordinates in a Cartesian coordinate system) and finds a linear function (a non-vertical straight line) that, as accurately as possible, predicts the dependent variable values as a function of the independent variables.
https://github.com/lovesaroha/regression-with-single-parameter
canvas html javascript linear-regression regression
Last synced: 3 days ago
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In statistics, simple linear regression is a linear regression model with a single explanatory variable.That is, it concerns two-dimensional sample points with one independent variable and one dependent variable (conventionally, the x and y coordinates in a Cartesian coordinate system) and finds a linear function (a non-vertical straight line) that, as accurately as possible, predicts the dependent variable values as a function of the independent variables.
- Host: GitHub
- URL: https://github.com/lovesaroha/regression-with-single-parameter
- Owner: lovesaroha
- License: gpl-3.0
- Created: 2021-09-08T17:00:53.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2021-10-01T10:57:31.000Z (about 3 years ago)
- Last Synced: 2024-01-26T05:14:19.277Z (10 months ago)
- Topics: canvas, html, javascript, linear-regression, regression
- Language: CSS
- Homepage: https://ml.lovesaroha.com/Regression-With-Single-Parameter
- Size: 51.8 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Regression-With-Single-Parameter
In statistics, simple linear regression is a linear regression model with a single explanatory variable.That is, it concerns two-dimensional sample points with one independent variable and one dependent variable (conventionally, the x and y coordinates in a Cartesian coordinate system) and finds a linear function (a non-vertical straight line) that, as accurately as possible, predicts the dependent variable values as a function of the independent variables.
Demo [lovesaroha/Regression-With-Single-Parameter](https://ml.lovesaroha.com/Regression-With-Single-Parameter)![image](https://raw.githubusercontent.com/lovesaroha/gimages/main/17.png)