The Application Of Support Vector Machines And Classification Model Comparison In The Survey Of Life Satisfaction

The classification problem in machine learning is one of the most important which is also known as model recognition.Support vector machine is a kind of classification model.The common classification algorithms include decision tree,logistic regression,random forest,na?ve Bayes and so on.This paper based in a survey of people's life focuses on the analysis of the key factors of life satisfaction and the degree of satisfaction of decision making.This part uses nonlinear support vector machine,decision tree,logistic regression building models and repeating ten times ten-fold cross validation method,analyzes the dataset and compares application effect.Analysis showed that older respondents on life satisfaction is higher;income level in a certain range and life satisfaction into positive correlation;leisure level,social services and other issue have also been respondents highly attention.