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LinearRegressionResults

so_models::regression

Struct LinearRegressionResults 

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pub struct LinearRegressionResults {
Show 16 fields
    pub coefficients: Array1<f64>,
    pub std_errors: Option<Array1<f64>>,
    pub t_values: Option<Array1<f64>>,
    pub p_values: Option<Array1<f64>>,
    pub rss: f64,
    pub tss: f64,
    pub r_squared: f64,
    pub r_squared_adj: f64,
    pub sigma: f64,
    pub df_residual: usize,
    pub df_model: usize,
    pub f_statistic: Option<f64>,
    pub f_p_value: Option<f64>,
    pub aic: Option<f64>,
    pub bic: Option<f64>,
    pub log_likelihood: Option<f64>,

}
Expand description

Results from fitting a linear regression model

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§coefficients: Array1<f64>

Estimated coefficients (including intercept if present)

§std_errors: Option<Array1<f64>>

Standard errors of coefficients

§t_values: Option<Array1<f64>>

t-statistics for coefficients

§p_values: Option<Array1<f64>>

p-values for coefficients

§rss: f64

Residual sum of squares

§tss: f64

Total sum of squares

§r_squared: f64

R-squared (coefficient of determination)

§r_squared_adj: f64

Adjusted R-squared

§sigma: f64

Residual standard error

§df_residual: usize

Degrees of freedom

§df_model: usize

Degrees of freedom of model

§f_statistic: Option<f64>

F-statistic

§f_p_value: Option<f64>

F-statistic p-value

§aic: Option<f64>

Akaike Information Criterion

§bic: Option<f64>

Bayesian Information Criterion

§log_likelihood: Option<f64>

Log-likelihood

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impl LinearRegressionResults

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pub fn summary(&self, feature_names: &[String]) -> String

Create a summary string similar to R’s summary()

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pub fn predict(&self, X: &Array2<f64>) -> Array1<f64>

Predict using fitted model

Trait Implementations§

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impl Clone for LinearRegressionResults

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fn clone(&self) -> LinearRegressionResults

Returns a duplicate of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for LinearRegressionResults

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more
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impl<'de> Deserialize<'de> for LinearRegressionResults

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fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>
where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer. Read more
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impl Serialize for LinearRegressionResults

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fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>
where __S: Serializer,

Serialize this value into the given Serde serializer. Read more

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🔬This is a nightly-only experimental API. (clone_to_uninit)
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