Several Classification Algorithms And Their Applications In Statistical Learning

It has been critical to mine mass data to get information we need in the Big Data time.Classification plays an important role in data mining and it builds a model by extracting valid data information and classifies the data of unknown categories into known categories.Many problems in real life can be regarded as classification problems,such as customer mining,commodity marketing,telecom fraud judgment and so on.Classification algorithms in Statistical Learning are effective tools to deal with classification problems.This paper introduces Logistic Regression,Support Vector Machine,Random Forest and Artificial Neural Network and which combined with the data preprocessing method and the Filter and Wrapper methods in the Feature Engineering.A systematic method for dealing with the actual classification problems is formed.The system classification methods in this paper play well in accurate marketing through the simulation of insurance customer data.