I have done a machine learning regression task. I am confused by the correlations and regression coefficient. The correlations of the datasets are depicted using seaborn library heatmap:
sns.heatmap(usa_housing_price.corr(), annot=True, cmap='coolwarm')
The regression coefficients are as follows:
coef = pd.DataFrame(linear_model.coef_, X.columns) coef.columns = ['Coefficients'] coef
My question is despite the "Avg. Area Income" is the most correlated feature with the "Price", it has less impact on "Price" in compare of other features?
How this tow parameter related to each other?