What would a passenger’s chance of survival be on the sinking Titanic?
train=read.csv("titanic_train.csv")
test=read.csv("titanic_test.csv")
train$Survived=factor(train$Survived)
train=na.omit(train)
test=na.omit(test)
model=randomForest(Survived~Pclass+Sex+Age+SibSp+Parch+Fare,ntree=500,importance=T,data=train)
predictions=predict(model,test)
titanic_predictions=read.csv('titanic_predictions.csv')
sum(titanic_predictions)/count(titanic_predictions)
Passengers have a 34% survival rate.
## R version 4.3.0 alpha (2023-04-01 r84141 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19045)
##
## Matrix products: default
##
##
## locale:
## [1] LC_COLLATE=English_United States.utf8
## [2] LC_CTYPE=English_United States.utf8
## [3] LC_MONETARY=English_United States.utf8
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.utf8
##
## time zone: America/New_York
## tzcode source: internal
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] randomForest_4.7-1.1 readxl_1.4.2 tidyselect_1.2.0
## [4] lubridate_1.9.2 forcats_1.0.0 stringr_1.5.0
## [7] dplyr_1.1.1 purrr_1.0.1 readr_2.1.4
## [10] tidyr_1.3.0 tibble_3.2.1 tidyverse_2.0.0
## [13] ggplot2_3.4.1
##
## loaded via a namespace (and not attached):
## [1] sass_0.4.5 utf8_1.2.3 generics_0.1.3 stringi_1.7.12
## [5] hms_1.1.3 digest_0.6.31 magrittr_2.0.3 evaluate_0.20
## [9] grid_4.3.0 timechange_0.2.0 fastmap_1.1.1 cellranger_1.1.0
## [13] jsonlite_1.8.4 fansi_1.0.4 scales_1.2.1 jquerylib_0.1.4
## [17] cli_3.6.1 rlang_1.1.0 munsell_0.5.0 withr_2.5.0
## [21] cachem_1.0.7 yaml_2.3.7 tools_4.3.0 tzdb_0.3.0
## [25] colorspace_2.1-0 vctrs_0.6.1 R6_2.5.1 lifecycle_1.0.3
## [29] pkgconfig_2.0.3 pillar_1.9.0 bslib_0.4.2 gtable_0.3.3
## [33] glue_1.6.2 xfun_0.38 rstudioapi_0.14 knitr_1.42
## [37] htmltools_0.5.5 rmarkdown_2.21 compiler_4.3.0