This project aims to identify the key factors that contributed to survival outcomes during the infamous 1912 Titanic disaster.
对年龄进行分类之后
Call:
glm(formula = Survived ~ ., family = "binomial", data = train_data)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 7.1041 1.2301 5.775 7.69e-09 ***
`Pclass2,3` -2.0011 0.3150 -6.353 2.11e-10 ***
Sexmale -2.8107 0.2692 -10.442 < 2e-16 ***
AgeGroupChild -3.8260 1.1800 -3.242 0.001185 **
AgeGroupTeenager -4.0772 1.2347 -3.302 0.000960 ***
AgeGroupYoungAdult -4.2590 1.1371 -3.746 0.000180 ***
AgeGroupAdult -4.4784 1.1554 -3.876 0.000106 ***
AgeGroupSenior -5.4430 1.3304 -4.091 4.29e-05 ***
SibSp -0.3375 0.1615 -2.090 0.036631 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 636.85 on 474 degrees of freedom
Residual deviance: 429.87 on 466 degrees of freedom
AIC: 447.87
Number of Fisher Scoring iterations: 5
Confusion Matrix and Statistics
Reference
Prediction 0 1
0 103 23
1 17 60
Accuracy : 0.803
95% CI : (0.7415, 0.8553)
No Information Rate : 0.5911
P-Value [Acc > NIR] : 1.077e-10
Kappa : 0.5878
Mcnemar's Test P-Value : 0.4292
Sensitivity : 0.8583
Specificity : 0.7229
Pos Pred Value : 0.8175
Neg Pred Value : 0.7792
Prevalence : 0.5911
Detection Rate : 0.5074
Detection Prevalence : 0.6207
Balanced Accuracy : 0.7906
'Positive' Class : 0
对年龄进行分类之前
Call:
glm(formula = Survived ~ ., family = "binomial", data = train_data)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 3.527633 0.512812 6.879 6.03e-12 ***
`Pclass2,3` -2.002717 0.304939 -6.568 5.11e-11 ***
Sexmale -2.630445 0.254367 -10.341 < 2e-16 ***
Age -0.026564 0.009358 -2.839 0.00453 **
SibSp -0.270880 0.142296 -1.904 0.05696 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 636.85 on 474 degrees of freedom
Residual deviance: 450.48 on 470 degrees of freedom
AIC: 460.48
Number of Fisher Scoring iterations: 4
Confusion Matrix and Statistics
Reference
Prediction 0 1
0 102 25
1 18 58
Accuracy : 0.7882
95% CI : (0.7255, 0.8423)
No Information Rate : 0.5911
P-Value [Acc > NIR] : 2.154e-09
Kappa : 0.556
Mcnemar's Test P-Value : 0.3602
Sensitivity : 0.8500
Specificity : 0.6988
Pos Pred Value : 0.8031
Neg Pred Value : 0.7632
Prevalence : 0.5911
Detection Rate : 0.5025
Detection Prevalence : 0.6256
Balanced Accuracy : 0.7744
'Positive' Class : 0
