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# HW-6 - Problem L7-1 1 Construct a C4.5 model that uses the...

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Problem L7-1: 1) Construct a C4.5 model that uses the inputs you suggested in problem L6-2 to predict the value of “symboling.” Use 3-fold cross validation. [Note, you can use Quinlan’s C4.5 code or one of the decision tree classifiers in weka. Solution: Attributes selected: 1. normalized-losses. 2. num-of-doors. 3. wheel-base. 4. length. 5. height. 6. symboling. Generating decision tree in WEKA using J48 pruned tree classifier with 3-fold cross validation: === Run information === Scheme: weka.classifiers.trees.J48 -C 0.25 -M 2 Relation: imports-85.csv- weka.filters.supervised.attribute.AttributeSelection- Eweka.attributeSelection.CfsSubsetEval- Sweka.attributeSelection.BestFirst -D 1 -N 5 Instances: 205 Attributes: 6 normalized-losses num-of-doors wheel-base length height symboling Test mode: 3-fold cross-validation === Classifier model (full training set) === J48 pruned tree ------------------ num-of-doors = two | height <= 50.2 | | wheel-base <= 97.3: 3 (16.0) | | wheel-base > 97.3: 0 (2.0/1.0)

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| height > 50.2 | | length <= 177.8 | | | wheel-base <= 95.7 | | | | wheel-base <= 89.5 | | | | | length <= 155.9: 2 (3.0) | | | | | length > 155.9: 3 (3.0) | | | | wheel-base > 89.5 | | | | | normalized-losses <= 85: 2 (3.28/0.28) | | | | | normalized-losses > 85 | | | | | | normalized-losses <= 154: 1 (21.24/0.6) | | | | | | normalized-losses > 154 | | | | | | | length <= 166.8: 2 (6.62/2.62) | | | | | | | length > 166.8: 1 (4.31) | | | wheel-base > 95.7 | | | | length <= 167.5: 0 (2.0) | | | | length > 167.5 | | | | | length <= 177.3 | | | | | | height <= 51: 1 (3.0/1.0) | | | | | | height > 51: 2 (12.0/1.0) | | | | | length > 177.3: 1 (2.44/0.44) | | length > 177.8 | | | wheel-base <= 99.2: 3 (4.0) | | | wheel-base > 99.2 | | | | height <= 52.8: 3 (3.0/1.0) | | | | height > 52.8: 0 (4.0/2.0) num-of-doors = four | wheel-base <= 101.2 | | height <= 51.6: 1 (10.56/1.0) | | height > 51.6 | | | wheel-base <= 97.2 | | | | wheel-base <= 95.1 | | | | | length <= 159.3: 0 (2.0) | | | | | length > 159.3: 1 (7.0/1.0) | | | | wheel-base > 95.1: 0 (28.0/1.0) | | | wheel-base > 97.2 | | | | length <= 176.6: 2 (7.0) | | | | length > 176.6 | | | | | length <= 184.6: 0 (11.56) | | | | | length > 184.6: 2 (3.0) | wheel-base > 101.2 | | normalized-losses <= 113 | | | length <= 188.8 | | | | normalized-losses <= 98: -1 (16.05/0.53) | | | | normalized-losses > 98: -2 (4.28/1.28) | | | length > 188.8 | | | | wheel-base <= 107.9: 1 (2.0/0.67) | | | | wheel-base > 107.9 | | | | | length <= 193.8: -1 (2.0) | | | | | length > 193.8 | | | | | | wheel-base <= 114.2: 0 (4.0) | | | | | | wheel-base > 114.2: -1 (2.33/0.67) | | normalized-losses > 113 | | | wheel-base <= 106.7 | | | | wheel-base <= 104.9: 0 (2.33/0.67) | | | | wheel-base > 104.9: 1 (2.33) | | | wheel-base > 106.7: 0 (10.67/0.33)
Number of Leaves : 31 Size of the tree : 61 Time taken to build model: 0.07 seconds === Stratified cross-validation === === Summary === Correctly Classified Instances 150 73.1707 % Incorrectly Classified Instances 55 26.8293 % Kappa statistic 0.6507 Mean absolute error 0.0916 Root mean squared error 0.2474 Relative absolute error 41.3845 % Root relative squared error 74.5523 %

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HW-6 - Problem L7-1 1 Construct a C4.5 model that uses the...

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