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how i can understand that how many instance this Titanic data set contain (base on the result.)

Hashmat_Sediqi123Hashmat_Sediqi123 Member Posts: 6 Contributor I

RuleModel(using Rule Induction operator).

if Sex = Male and Passenger Fare ≤ 26.269 then No  (57 / 367)
if Sex = Female and Passenger Class = First then Yes  (97 / 4)
if Sex = Male and Passenger Fare > 31.137 then No  (33 / 90)
if Passenger Class = Second and Age ≤ 28.500 then Yes  (36 / 4)
if Passenger Fare ≤ 24.808 and Passenger Fare > 15.373 and Age > 29.441 then Yes  (18 / 3)
if Passenger Fare ≤ 14.281 then Yes  (68 / 40)
if Passenger Class = Third and Passenger Fare > 23.746 then No  (1 / 23)
if Passenger Class = Second and Passenger Fare > 30.375 then Yes  (4 / 0)
if No of Parents or Children on Board ≤ 0.500 and Age ≤ 30.441 and Passenger Fare ≤ 28.710 and Age > 28.500 then No  (1 / 8)
if Age ≤ 54 then Yes  (33 / 22)
if Age ≤ 71 then No  (0 / 6)
else Yes  (0 / 0)

correct: 750 out of 915 training examples.

Answers

  • Telcontar120Telcontar120 Moderator, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 1,625   Unicorn
    Your question is a bit ambiguous, what specific count are you asking about?
    In the output above, each rule row shows the count in parentheses for each of the classes where the majority class corresponds to the prediction.
    Then at the bottom it tells you the total number of correct predictions out of the total number of training examples.  So in this case, there were 915 training examples used.
    Brian T.
    Lindon Ventures 
    Data Science Consulting from Certified RapidMiner Experts
    Hashmat_Sediqi123
  • Hashmat_Sediqi123Hashmat_Sediqi123 Member Posts: 6 Contributor I
    @Telcontar120
    thanks for the reply , i got it .
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