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