/ml_taller4

Primary LanguageR

Naive Bayes Classifier for Discrete Predictors

Call:
naiveBayes.default(x = train_data[3:9], y = train_data$Survived)

A-priori probabilities:

0 (Not survived) 1 (Survived)
0.6175478 0.3824522

Conditional probabilities:

                                  Pcclass (Ticket class)

1 (Upper class) 2 (Middle class) 3 (Lower class)
0 (Not survived) 0.1457195 0.1766849 0.6775956
1 (Survived) 0.3941176 0.2558824 0.3500000

                                  Sex

female male
0 (Not survived) 0.1475410 0.8524590
1 (Survived) 0.6794118 0.3205882

                                  Age

[0.42,25) [25,31) [31,80]
0 (Not survived) 0.2914390 0.3825137 0.3260474
1 (Survived) 0.3470588 0.2941176 0.3588235

                                  Sibsp (# of siblings / spouses aboard the Titanic)

0 1 2 3 4 5 8
0 (Not survived) 0.724954463 0.176684882 0.027322404 0.021857923 0.027322404 0.009107468 0.012750455
1 (Survived) 0.611764706 0.329411765 0.038235294 0.011764706 0.008823529 0.000000000 0.000000000

                                  Parch (# of parents / children aboard the Titanic)

0 1 2 3 4 5 6
0 (Not survived) 0.810564663 0.096539162 0.072859745 0.003642987 0.007285974 0.007285974 0.001821494
1 (Survived) 0.679411765 0.191176471 0.117647059 0.008823529 0.000000000 0.002941176 0.000000000

                                  Fare (Passenger fare)

[0,8.66) [8.66,26) [26,512]
0 (Not survived) 0.4280510 0.3060109 0.2659381
1 (Survived) 0.1764706 0.3000000 0.5235294

                                  Embarked (Port of Embarkation)

C (Cherbourg) Q (Queenstown) S (Southampton)
0 (Not survived) 0.13661202 0.08561020 0.77777778
1 (Survived) 0.27352941 0.08823529 0.63823529

test_pred
[1] 0 0 0 0 1 0 0 1 0 0 0 0 1 0 1 1 0 0 0 0 1 0 1 1 1 0 1 0 0 0 0 0 1
[34] 1 1 0 0 0 0 0 0 0 0 1 1 0 1 0 1 1 1 0 1 1 0 0 0 0 0 1 0 0 0 0 1 1
[67] 0 0 1 1 0 0 0 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 1 1 0 1 0 1 0 1 0 0
[100] 0 1 0 0 0 1 0 0 0 0 0 0 0 1 0 1 0 0 1 1 1 1 0 1 0 0 1 0 1 0 0 0 1
[133] 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 0 0 1 0 0 1 0 0 1 0 0 1 0 0
[166] 1 1 0 1 0 0 0 0 0 0 1 1 1 1 1 0 1 1 0 1 0 1 0 0 0 0 0 0 0 0 0 1 0
[199] 0 0 1 0 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 1 1 0 1 0 1 0 1 1 0 0 0 0 0
[232] 1 0 0 1 0 1 0 1 1 1 1 1 0 0 1 1 1 1 1 1 0 1 0 0 0 0 0 1 0 0 0 1 1
[265] 0 0 0 0 0 0 1 0 1 1 0 1 0 0 0 0 0 0 0 1 1 0 0 1 0 0 0 0 0 1 0 0 1
[298] 0 0 0 0 0 0 0 0 1 1 0 1 1 0 0 0 0 1 0 1 0 0 0 0 0 0 0 1 0 1 1 0 0
[331] 1 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 1 1 0 1 0 0 1 0 1 1
[364] 0 1 1 0 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 1
[397] 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 1 0 0 1 0 0 0
Levels: 0 1