Find Most Important Features For Machine Learning in Python

Today we learn how to find the most important features when doing machine learning in Python.

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[NIKA-zgen]

What you also can do is a Lasso Regression and increase the alpha(lambda) from zero to x and then you will see which feature will fall to zero.

[Richardred]

There is also statistical function from scipy called stats.pearsonr() which basicly return two parameters
correlation_coefficient, p_value = stats.pearsonr(x, y).
correlation_coefficient is the same thing we see in df.corr() and a p-value is for statical test.
A low p-value indicates that the correlation observed in the sample is unlikely to have occurred by random chance alone.
for example with p-value = 0.05 we are 95% sure that there is a correlation between the variables.