保险风险预测数据集insurance.csv

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age,sex,bmi,children,smoker,region,charges

19,female,27.9,0,yes,southwest,16884.924

18,male,33.77,1,no,southeast,1725.5523

28,male,33,3,no,southeast,4449.462

33,male,22.705,0,no,northwest,21984.47061

32,male,28.88,0,no,northwest,3866.8552

31,female,25.74,0,no,southeast,3756.6216

46,female,33.44,1,no,southeast,8240.5896

37,female,27.74,3,no,northwest,7281.5056

37,male,29.83,2,no,northeast,6406.4107

60,female,25.84,0,no,northwest,28923.13692

25,male,26.22,0,no,northeast,2721.3208

62,female,26.29,0,yes,southeast,27808.7251

23,male,34.4,0,no,southwest,1826.843

56,female,39.82,0,no,southeast,11090.7178

27,male,42.13,0,yes,southeast,39611.7577

19,male,24.6,1,no,southwest,1837.237

52,female,30.78,1,no,northeast,10797.3362

23,male,23.845,0,no,northeast,2395.17155

56,male,40.3,0,no,southwest,10602.385

30,male,35.3,0,yes,southwest,36837.467

60,female,36.005,0,no,northeast,13228.84695

30,female,32.4,1,no,southwest,4149.736

18,male,34.1,0,no,southeast,1137.011

34,female,31.92,1,yes,northeast,37701.8768

37,male,28.025,2,no,northwest,6203.90175

59,female,27.72,3,no,southeast,14001.1338