# simplemlplus
> Version: 1.0.1
Simple machine learning one-liners.
## Headless Mode
All functions create plots, useful for seeing how they work. To use a headless version (no plot), just import them from `simplemlplus.headless` instead of `simplemlplus`.
## Plot Only
If you just want to see the visual representation, simply call the function without assigning it to a variable.
```python
import simplemlplus
linear_regression(6, [5, 2, 7, 8], [4, 2, 4, 8])
```
## Linear Regression
```python
linear_regression(x: int, x_data: list, y_data: list)
Returns:
{
"prediction": predicted value,
"r", relationship, how well this regression fits the model
}
```
Both `x_data` and `y_data` have default values if you want to play around with existing data.
### Example Use
```python
import simplemlplus
data = linear_regression(10, [1, 2, 3, 4], [1, 2, 3, 4])
```
## Polynomial Regression
```python
import simplemlplus
data = polynomial_regression(x: int, x_data: list, y_data: list)
Returns:
{
"prediction": predicted value,
"r", relationship^2, how well this regression fits the model
}
```
Both `x_data` and `y_data` have default values if you want to play around with existing data.
### Example Use
```python
polynomial_regression(10, [1, 2, 3, 4], [1, 2, 3, 4])
```
## Contribuiting
The repo is `XenonPy/ai`. Feel free to open an issue/PR for any changes.
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"description": "# simplemlplus\n> Version: 1.0.1\n\nSimple machine learning one-liners.\n## Headless Mode\nAll functions create plots, useful for seeing how they work. To use a headless version (no plot), just import them from `simplemlplus.headless` instead of `simplemlplus`.\n## Plot Only\nIf you just want to see the visual representation, simply call the function without assigning it to a variable.\n```python\nimport simplemlplus\nlinear_regression(6, [5, 2, 7, 8], [4, 2, 4, 8])\n```\n\n## Linear Regression\n```python\nlinear_regression(x: int, x_data: list, y_data: list)\n\nReturns:\n\n{\n \"prediction\": predicted value,\n \"r\", relationship, how well this regression fits the model\n}\n```\nBoth `x_data` and `y_data` have default values if you want to play around with existing data.\n### Example Use\n```python\nimport simplemlplus\ndata = linear_regression(10, [1, 2, 3, 4], [1, 2, 3, 4])\n```\n\n## Polynomial Regression\n```python\nimport simplemlplus\ndata = polynomial_regression(x: int, x_data: list, y_data: list)\n\nReturns:\n\n{\n \"prediction\": predicted value,\n \"r\", relationship^2, how well this regression fits the model\n}\n```\nBoth `x_data` and `y_data` have default values if you want to play around with existing data.\n### Example Use\n```python\npolynomial_regression(10, [1, 2, 3, 4], [1, 2, 3, 4])\n```\n\n## Contribuiting\nThe repo is `XenonPy/ai`. Feel free to open an issue/PR for any changes.\n\n",
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