# emel v0.3.0 Emel.Ml.LinearRegression View Source

A linear approach to modelling the relationship between a dependent variable and one or more independent variables.

# Link to this section Summary

## Functions

Returns the linear function that predicts the value of the dependent variable

The set of predictor function’s coefficients based on observations (`points`)

# Link to this section Functions

Link to this function predictor(dataset, independent_variables, dependent_variable) View Source

Returns the linear function that predicts the value of the dependent variable.

## Examples

``````iex> f = Emel.Ml.LinearRegression.predictor([%{x1: 1.794638, x2: 15.15426     , y:   5.10998918E-1},
...>                                         %{x1: 3.220726, x2: 229.6516     , y: 105.6583692    },
...>                                         %{x1: 5.780040, x2:   3.480201e+3, y:   1.77699E3    }],
...>                                        [:x1, :x2], :y)
...> f.(%{x1: 3.0, x2: 230.0})
106.74114058686602``````
Link to this function regression_coefficients(points) View Source

The set of predictor function’s coefficients based on observations (`points`).

## Examples

``````iex> Emel.Ml.LinearRegression.regression_coefficients([[1.794638, 15.15426     ,   5.10998918E-1],
...>                                                   [3.220726, 229.6516     , 105.6583692    ],
...>                                                   [5.780040,   3.480201e+3,   1.77699E3    ]])
{:ok, [0.00834962613023635, -4.0888400103672184, 0.5173883086601628]}

iex> Emel.Ml.LinearRegression.regression_coefficients([[1.0, 1.0 ],
...>                                                   [2.0, 2.0 ],
...>                                                   [3.0, 1.3 ],
...>                                                   [4.0, 3.75],
...>                                                   [5.0, 2.25]])
{:ok, [0.785, 0.425]}``````