=== Run information === Scheme:weka.classifiers.rules.JRip -F 3 -N 2.0 -O 2 -S 1 Relation: crime_violent_WEKA-weka.filters.unsupervised.attribute.Remove-R102-108,110-114,116-119-weka.filters.unsupervised.attribute.Discretize-unset-class-temporarily-B10-M-1.0-R102,103-weka.filters.unsupervised.attribute.Remove-R102 Instances: 1901 Attributes: 102 [list of attributes omitted] Test mode:5-fold cross-validation === Classifier model (full training set) === JRIP rules: =========== (pctImmig3 >= 2.88) and (pctBornStateResid <= 36.4) and (pctForeignBorn >= 24.81) => TotalCrimeOutlier='(0.9-inf)' (25.0/2.0) (pctMaleNevMar >= 37.01) and (persPerFam >= 3.15) and (pctNotSpeakEng <= 2.63) and (pctPersOwnOccup <= 52.44) => TotalCrimeOutlier='(0.9-inf)' (16.0/3.0) (pctWorkMom18 <= 60) and (pctWorkMom18 <= 56.42) and (landArea <= 7.5) => TotalCrimeOutlier='(0.9-inf)' (27.0/9.0) (pctOccupManu <= 5.32) and (pctHousOccup <= 93.32) and (pctPoverty >= 4.07) and (landArea <= 17) => TotalCrimeOutlier='(0.9-inf)' (11.0/1.0) (pctSmallHousUnits >= 61.09) and (landArea >= 21.1) and (pctFemDivorc <= 16.03) => TotalCrimeOutlier='(0.9-inf)' (21.0/9.0) (perHoush >= 3.21) and (pctEmploy <= 50.57) => TotalCrimeOutlier='(0.9-inf)' (19.0/7.0) (pctCollGrad >= 53.58) and (pctBornStateResid <= 44.12) and (otherPerCap >= 21104) => TotalCrimeOutlier='(0.9-inf)' (9.0/0.0) (pctCollGrad >= 46.09) and (pop <= 11714) => TotalCrimeOutlier='(0.9-inf)' (11.0/4.0) (landArea >= 177.4) and (persPerOwnOccup >= 2.71) => TotalCrimeOutlier='(0.9-inf)' (11.0/2.0) (pctWhite <= 39.68) and (houseVacant <= 426) => TotalCrimeOutlier='(0.9-inf)' (7.0/2.0) (persHomeless >= 792) => TotalCrimeOutlier='(0.9-inf)' (3.0/0.0) (pctForeignBorn >= 10.86) and (pctHousWOplumb >= 0.59) and (pctSmallHousUnits >= 65.85) => TotalCrimeOutlier='(0.8-0.9]' (23.0/9.0) (ownHousUperQ >= 244500) and (pctEmploy <= 63.74) and (pctFgnImmig3 >= 17.39) => TotalCrimeOutlier='(0.8-0.9]' (12.0/2.0) (pctOccupManu <= 6.13) and (whitePerCap >= 35558) => TotalCrimeOutlier='(0.8-0.9]' (10.0/2.0) (pctMaleNevMar >= 33.88) and (pop <= 21249) and (perHoush >= 3.06) => TotalCrimeOutlier='(0.8-0.9]' (16.0/5.0) (pop <= 13364) and (pctNotHSgrad >= 35.53) and (persEmergShelt >= 1) => TotalCrimeOutlier='(0.8-0.9]' (13.0/3.0) (pctSpeakOnlyEng <= 80.21) and (pop <= 16829) and (pctEmploy >= 65.24) => TotalCrimeOutlier='(0.8-0.9]' (14.0/4.0) (pctPersOwnOccup >= 81.14) and (asianPerCap >= 65560) => TotalCrimeOutlier='(0.8-0.9]' (5.0/0.0) (pctLowEdu >= 20.1) and (pctUnemploy >= 10.91) and (pctUsePubTrans >= 0.23) => TotalCrimeOutlier='(0.8-0.9]' (15.0/6.0) (pop <= 17457) and (pctWdiv <= 26.62) and (persPerOwnOccup <= 2.57) => TotalCrimeOutlier='(0.6-0.7]' (18.0/5.0) (pctEmployMfg <= 14.85) and (pop <= 16392) and (persPerRenterOccup >= 2.57) => TotalCrimeOutlier='(0.7-0.8]' (39.0/19.0) (pctFgnImmig8 >= 32.29) and (NAperCap <= 1957) => TotalCrimeOutlier='(0.7-0.8]' (31.0/14.0) (pctWhite <= 70.45) and (landArea <= 14.3) and (pctNotSpeakEng <= 1.14) => TotalCrimeOutlier='(0.7-0.8]' (32.0/14.0) (pop <= 17406) and (pctAsian <= 0.42) and (pctUnemploy >= 5.82) and (pctWorkMom6 >= 62.08) => TotalCrimeOutlier='(0.5-0.6]' (27.0/8.0) => TotalCrimeOutlier='(-inf-0.1]' (1486.0/1245.0) Number of Rules : 25 Time taken to build model: 8.76 seconds === Stratified cross-validation === === Summary === Correctly Classified Instances 328 17.2541 % Incorrectly Classified Instances 1573 82.7459 % Kappa statistic 0.0585 Mean absolute error 0.1727 Root mean squared error 0.3012 Relative absolute error 96.1699 % Root relative squared error 100.5202 % Total Number of Instances 1901 === Detailed Accuracy By Class === TP Rate FP Rate Precision Recall F-Measure ROC Area Class 1 0.829 0.149 1 0.259 0.591 '(-inf-0.1]' 0 0 0 0 0 0.557 '(0.1-0.2]' 0 0 0 0 0 0.576 '(0.2-0.3]' 0 0 0 0 0 0.555 '(0.3-0.4]' 0 0 0 0 0 0.538 '(0.4-0.5]' 0.018 0.011 0.174 0.018 0.032 0.526 '(0.5-0.6]' 0.006 0.009 0.059 0.006 0.011 0.505 '(0.6-0.7]' 0.031 0.024 0.128 0.031 0.05 0.527 '(0.7-0.8]' 0.121 0.032 0.267 0.121 0.167 0.618 '(0.8-0.9]' 0.373 0.038 0.459 0.373 0.412 0.714 '(0.9-inf)' Weighted Avg. 0.173 0.115 0.117 0.173 0.09 0.567 === Confusion Matrix === a b c d e f g h i j <-- classified as 241 0 0 0 0 0 0 0 0 0 | a = '(-inf-0.1]' 162 0 0 0 0 1 1 0 1 4 | b = '(0.1-0.2]' 184 0 0 0 0 1 0 0 2 1 | c = '(0.2-0.3]' 176 0 0 0 0 2 1 2 2 2 | d = '(0.3-0.4]' 194 0 0 0 0 0 1 8 3 3 | e = '(0.4-0.5]' 196 0 0 0 0 4 5 8 9 5 | f = '(0.5-0.6]' 150 0 0 0 0 6 1 3 9 3 | g = '(0.6-0.7]' 157 0 0 0 0 2 2 6 12 16 | h = '(0.7-0.8]' 88 0 0 0 0 5 4 16 20 32 | i = '(0.8-0.9]' 69 0 0 0 0 2 2 4 17 56 | j = '(0.9-inf)'