Who Survived on the Titanic?
Titanic ny american The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912...
2027
31/12
 
  Partecipanti 39 Sottomissioni 1526  
 

The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew.

In this challenge, we ask you to apply the tools of statistical learning to predict which passengers survived the tragedy.

See Kaggle competition “Titanic: Machine Learning from Disaster”.

For each passenger in the test set, you must predict whether or not they survived the sinking ( 0 for deceased, 1 for survived ). Your score is the percentage of passengers you correctly predict.

During the competition, the leaderboard displays your partial score, which is the % of correct classifications for 200 (random) passengers of the test set.
At the end of the contest, the leaderboard will display the final score, which is the % of correct classifications for the remaining 218 passengers of the test set. The final score will determine the final winner. This method prevents users from overfitting to the leaderboard.

Maximum team size = 3

train <- read.csv(“train.csv”, stringsAsFactors = F)
test <- read.csv(“test.csv”, stringsAsFactors = F)

fit = glm(Survived ~ Sex, family=“binomial”, data=train)
phat = predict(fit, newdata=test, type=“response”)
yhat = ifelse(phat > 0.5, 1,0)

write.table(file=“mySubmission.txt”, yhat, row.names = FALSE, col.names = FALSE)

You are given with two data sets:

train.csv: 891 passengers, 11 predictors and the response (survived or perished)
test.csv: 418 passengers, 11 predictors




Training set train.csv
80 KB
Test set test.csv
40 KB
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# Nome Punteggio Prove Ultima prova
1 v.angius1 PARZIALE 83.00% 55 14.11.2016
08:38
2 m.monaldi PARZIALE 83.00% 30 14.11.2016
17:39
3 n.vanderhart PARZIALE 83.00% 19 14.11.2016
08:42
4 m.fumagalli68 PARZIALE 83.00% 6 14.11.2016
15:59
5 riccardo.parviero PARZIALE 82.50% 83 15.11.2016
15:51
6 d.marzagora PARZIALE 82.50% 32 15.11.2016
15:57
7 elisa.lucci PARZIALE 82.50% 31 15.11.2016
15:59
8 gramaticamarco PARZIALE 82.00% 67 15.11.2016
15:58
9 r.lavelli1 PARZIALE 82.00% 57 15.11.2016
12:47
10 s.dalessio PARZIALE 82.00% 56 15.11.2016
12:39
11 D.Pagani PARZIALE 82.00% 41 15.11.2016
16:15
12 f.giorgini PARZIALE 82.00% 34 15.11.2016
16:42
13 d.gualtieri5 PARZIALE 82.00% 23 15.11.2016
12:35
14 d.caldara1 PARZIALE 82.00% 13 15.11.2016
16:41
15 A.Pizzocri PARZIALE 82.00% 5 15.11.2016
16:43
16 f.pirola13 PARZIALE 81.50% 140 15.11.2016
14:18
17 f.vitti1 PARZIALE 81.50% 121 15.11.2016
17:58
18 m.rosa18 PARZIALE 81.50% 101 14.11.2016
16:03
19 a.galli33 PARZIALE 81.50% 77 15.11.2016
15:25
20 r.monetti1 PARZIALE 81.50% 77 15.11.2016
15:34
21 chiara.gorla PARZIALE 81.50% 2 15.11.2016
14:43
22 f.bogni PARZIALE 80.50% 10 31.10.2016
14:21
23 gpolp PARZIALE 80.00% 102 15.11.2016
13:34
24 p.maranzano PARZIALE 80.00% 48 14.11.2016
08:24
25 e.fabrizi1 PARZIALE 80.00% 47 15.11.2016
13:10
26 f.facciuto PARZIALE 80.00% 17 15.11.2016
13:35
27 h.akyirefi PARZIALE 80.00% 6 02.11.2016
21:08
28 a.guevara PARZIALE 79.00% 40 12.11.2016
16:10
29 adriana.algisi PARZIALE 78.50% 82 15.11.2016
11:10
30 c.galimberti19 PARZIALE 78.50% 28 11.11.2016
15:56
31 m.fogliata PARZIALE 78.50% 22 15.11.2016
12:17
32 l.sella PARZIALE 78.50% 14 15.11.2016
12:52
33 g.andromede PARZIALE 78.50% 10 15.11.2016
13:38
34 a.brambilla73 PARZIALE 78.50% 8 15.11.2016
13:10
35 p.barberis1 PARZIALE 78.50% 6 09.11.2016
15:37
36 solari.aldo PARZIALE 77.50% 15 15.11.2016
15:45