scikit learn lasso regression
from sklearn import linear_model
reg = linear_model.Lasso(alpha=0.1).fit(X, y)
reg.fit(X, y) #We can fit Lasso to the dataset in this way too
clf.score(X, y) #Return the mean accuracy on the given test data and labels
cfl.predict(X) #Return the predictions
#Regression Metrics
#Mean Absolute Error
from sklearn.metrics import mean_absolute_error
mean_absolute_error(y_true, y_pred)
#Mean Squared Error
from sklearn.metrics import mean_squared_error
mean_squared_error(y_true, p_pred)
#R2 Score
from sklearn.metrics import r2_score
r2_score(y_true, y_pred)
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