notebooks/model.py
def adj_r2(r2_score, num_observations, num_parameters):
    """Calculate the Adjusted R-Squared value

    Args: 
        r2_score (int): R-Squared value to adjust
        num_observations (int): Number of observations used in model
        num_parameters (int): Number of parameters used in model

    Returns:
        adj_r2 (float): Adjusted R-Squared value
    """
    return r2_score-(num_parameters-1)/(num_observations-num_parameters)*(1-r2_score)
Calculate the Adjusted R-Squared value

    Args: 
        r2_score (int): R-Squared value to adjust
        num_observations (int): Number of observations used in model
        num_parameters (int): Number of parameters used in model

    Returns:
        adj_r2 (float): Adjusted R-Squared value
    
Calculate the Adjusted R-Squared value
Calculate the Adjusted R - Squared value
def adj_r2(r2_score, num_observations, num_parameters):
    return r2_score-(num_parameters-1)/(num_observations-num_parameters)*(1-r2_score)
def adj_r2 ( r2_score , num_observations , num_parameters ) : return r2_score - ( num_parameters - 1 ) / ( num_observations - num_parameters ) * ( 1 - r2_score )
Calculate the Adjusted R-Squared value
Calculate the Adjusted R - Squared value
"""Calculate the Adjusted R-Squared value

    Args: 
        r2_score (int): R-Squared value to adjust
        num_observations (int): Number of observations used in model
        num_parameters (int): Number of parameters used in model

    Returns:
        adj_r2 (float): Adjusted R-Squared value
    """
adj_r2 (float): Adjusted R-Squared value
adj_r2 ( float ) : Adjusted R - Squared value
r2_score
R-Squared value to adjust
R - Squared value to adjust
num_observations
Number of observations used in model
Number of observations used in model
num_parameters
Number of parameters used in model
Number of parameters used in model