OLS Stats Model (Ordinary Least Square)

• OLS is a stats model, which will help us in identifying the more significant features that can have an influence on the output.

• OLS model in python is executed as:

  • lm = smf.ols(formula = 'Sales ~ am+constant', data = data).fit() lm.conf_int() lm.summary()

• The higher the t-value for the feature, the more significant the feature is to the output variable.

• The p-value plays a role in rejecting the Null hypothesis(The null hypothesis states the features has zero significance on the target variable.).

• If the p-value is less than 0.05(95% confidence interval) for a feature, then we can consider the feature to be significant.