what is the difference between regression and random forest.?

where is random forest more effective ?

# What is the difference between regression and random forest.? where is random forest more effective?

**Sunil0108**#1

**syed.danish**#2

Regression analysis is statistical process for estimating the relationships among variables and random forest is machine learning method capable of performing both regression and classification tasks .In Regression analysis we fit a curve / line to the data points, in such a manner that the error between the value of fitted regression model at each point is and the actual value is minimized . There are different types of regression analysis, go through this article to gain some insights. :

Where as in random forest we make multiple decison trees. To classify a new object based on attributes, each tree gives a classification and we say the tree “votes” for that class. The forest chooses the classification having the most votes (over all the trees in the forest) and in case of regression, it takes the average of outputs by different trees.

Take a look at this article :

Random Forest is able to discover more complex relation at the cost of time. If it’s established, that your variable has a linear relationship from the outcome, you will probably get similar results with both RF and linear regression . Its advisable to first explore the data and try to extract some relation between independent and dependent variable then apply the suitable method.

Regards,

Danish