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Added example of using Titanic survival data from Kaggle

Browse source 
https://www.kaggle.com/c/titanic-gettingStarted
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Joshua Eckroth 2013-08-06 19:44:23 -04:00
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README.md
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@ -491,6 +491,201 @@ user> clustered-ds
...
```
## Example: Predicting survival on the Titanic
https://www.kaggle.com/c/titanic-gettingStarted
First globally replace all double quoted strings `""foo""` with
backslash quoted strings: `\"foo\"`. Weka does not handle the former.
```clojure
user> (def titanicds (load-instances :csv "file:///home/josh/git/clj-ml/titanic-train.csv"))
user> titanicds
#<Instances @relation stream
@attribute PassengerId numeric
@attribute Survived numeric
@attribute Pclass numeric
@attribute Name {'Braund, Mr. Owen Harris','Cumings, Mrs. John Bradley (Florence Briggs Thayer)', ...}
@attribute Sex {male,female}
@attribute Age numeric
@attribute SibSp numeric
@attribute Parch numeric
@attribute Ticket {'A/5 21171','PC 17599','STON/O2. 3101282',113803.0, ...}
@attribute Fare numeric
@attribute Cabin {C85,C123,E46,G6,C103,D56,A6,'C23 C25 C27', ...}
@attribute Embarked {S,C,Q}
@data
1,0,3,'Braund, Mr. Owen Harris',male,22,1,0,'A/5 21171',7.25,?,S
2,1,1,'Cumings, Mrs. John Bradley (Florence Briggs Thayer)',female,38,1,0,'PC 17599',71.2833,C85,C
3,1,3,'Heikkinen, Miss. Laina',female,26,0,0,'STON/O2. 3101282',7.925,?,S
4,1,1,'Futrelle, Mrs. Jacques Heath (Lily May Peel)',female,35,1,0,113803.0,53.1,C123,S
5,0,3,'Allen, Mr. William Henry',male,35,0,0,373450.0,8.05,?,S
6,0,3,'Moran, Mr. James',male,?,0,0,330877.0,8.4583,?,Q
7,0,1,'McCarthy, Mr. Timothy J',male,54,0,0,17463.0,51.8625,E46,S
8,0,3,'Palsson, Master. Gosta Leonard',male,2,3,1,349909.0,21.075,?,S
9,1,3,'Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)',female,27,0,2,347742.0,11.1333,?,S
10,1,2,'Nasser, Mrs. Nicholas (Adele Achem)',female,14,1,0,237736.0,30.0708,?,C
11,1,3,'Sandstrom, Miss. Marguerite Rut',female,4,1,1,'PP 9549',16.7,G6,S
...
>
#'user/titanicds
user> (def titanicds (dataset-set-class titanicds :Survived))
#'user/titanicds
user> (dataset-class-index titanicds)
1
user> (def titanicds (make-apply-filter :numeric-to-nominal
{:attributes [:Survived]}
titanicds))
#'user/titanicds
user> titanicds
#<Instances @relation stream-weka.filters.unsupervised.attribute.NumericToNominal-R2
@attribute PassengerId numeric
@attribute Survived {0,1}
@attribute Pclass numeric
...
>
user> (def titanicds (make-apply-filter :remove-attributes
{:attributes [:PassengerId :Name :Ticket :Cabin]}
titanicds))
#'user/titanicds
user> titanicds
#<Instances @relation 'stream-weka.filters.unsupervised.attribute.NumericToNominal...'
@attribute Survived {0,1}
@attribute Pclass numeric
@attribute Sex {male,female}
@attribute Age numeric
@attribute SibSp numeric
@attribute Parch numeric
@attribute Fare numeric
@attribute Embarked {S,C,Q}
@data
0,3,male,22,1,0,7.25,S
1,1,female,38,1,0,71.2833,C
1,3,female,26,0,0,7.925,S
1,1,female,35,1,0,53.1,S
0,3,male,35,0,0,8.05,S
0,3,male,?,0,0,8.4583,Q
...
>
user> (dataset-class-index titanicds)
0
user> (dataset-class-name titanicds)
:Survived
user> (def evaluation (classifier-evaluate (make-classifier :decision-tree :random-forest)
:cross-validation titanicds 10))
#'user/evaluation
user> (println (:summary evaluation))
Correctly Classified Instances 727 81.5937 %
Incorrectly Classified Instances 164 18.4063 %
Kappa statistic 0.6039
Mean absolute error 0.2409
Root mean squared error 0.3819
Relative absolute error 50.9302 %
Root relative squared error 78.532 %
Total Number of Instances 891
nil
user> (println (:confusion-matrix evaluation))
=== Confusion Matrix ===
a b <-- classified as
483 66 | a = 0
98 244 | b = 1
nil
```
Ok, looks good, let's try training on the full training data and
testing on the testing data.
```clojure
user> (def titanic-testds (load-instances :csv "file:///home/josh/git/clj-ml/titanic-test.csv"))
user> (def titanic-test-passids (map (comp int :PassengerId)
(dataset-as-maps titanic-testds)))
#'user/titanic-test-passids
user> titanic-test-passids
(892 893 894 895 896 897 898 899 900 ...)
user> (def titanic-testds (->> titanic-testds
(make-apply-filter :remove-attributes
{:attributes [:PassengerId :Name :Ticket :Cabin]})
(make-apply-filter :add-attribute
{:type :nominal :name :Survived
:column 0 :labels ["0" "1"]})))
#'user/titanic-testds
user> (def titanic-testds (dataset-set-class titanic-testds :Survived))
#'user/titanic-testds
user> titanic-testds
#<Instances @relation 'stream-weka.filters.unsupervised.attribute.Remove...'
@attribute Survived {0,1}
@attribute Pclass numeric
@attribute Sex {male,female}
@attribute Age numeric
@attribute SibSp numeric
@attribute Parch numeric
@attribute Fare numeric
@attribute Embarked {Q,S,C}
@data
?,3,male,34.5,0,0,7.8292,Q
?,3,female,47,1,0,7,S
?,2,male,62,0,0,9.6875,Q
?,3,matitanle,27,0,0,8.6625,S
?,3,female,22,1,1,12.2875,S
?,3,male,14,0,0,9.225,S
?,3,female,30,0,0,7.6292,Q
...
>
user> (def classifier (classifier-train (make-classifier :decision-tree :random-forest) titanicds))
#'user/classifier
user> (def preds (for [instance (dataset-seq titanic-testds)]
(name (classifier-classify classifier instance))))
#'user/preds
user> preds
("0" "1" "0" "0" "0" "0" "1" "0" "0" "0" ...)
#'user/preds
user> (spit "titanic-predictions.csv"
(clojure.string/join "\n" (cons "Survived,PassengerId"
(map (fn [c1 c2] (format "%s,%d" c1 c2))
preds titanic-test-passids))))
nil
user> (println (slurp "titanic-predictions.csv"))
Survived,PassengerId
0,892
1,893
0,894
0,895
0,896
0,897
1,898
0,899
0,900
0,901
0,902
...
```
## Thanks YourKit!
YourKit is kindly supporting open source projects with its