How to check linear reliance between dependent variable and independent variables? Because so as to make Linear Regression model in Python we have to use (as I suppose) only variables which are: 1. correlated with dependent variable 2. independent variables which are not correlated with other independent variables 3. independent variables with linear reliance with dependent variables ? Please give me the code which is able to chech linear reliance in Python
You can use pandas for that:
df = pd.DataFrame({'feature one': [1,2,3,5,2,3],
'feature two': [5,10,18,23,16,20],
'feature three': [-23,-4,1,29,2,112],
'result': [10,20,30,50,20,30]})
print(df)
print(df.corr())
You will see that feature one
has the biggest correlation with result, then feature two
and then feature three
. You can also check out the correlation between each feature.
So, for your linear model I would chose first and second feature
If values are close to -1 or 1, that means that there is big correlation between features, if values are close to 0, that means that that there is no correlation.
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