where 𝑦 is the actual value and 𝑦 ′ is the value of best fitted line. By Lasso regression we have calculated the slope (m) value for each feature. 𝜆 is a constant and considering its value equal to one, the slope for each feature has been established. Those features having m value equal to zero were considered as irrelevant and those features were dropped. The lasso regression helped to shrink the feature by 64%. The selection of features based on feature importance has shown in the