| 1 | TYA 0.7 (for J116) loaded. Copyright (c) 1997,98 The TYA Team
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| 2 | Building classifier and saving it...
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| 3 | Loading data...
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| 4 | Counting positive examples...
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| 5 | Looking for missed keyphrases in the dataset...
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| 6 | Found 130 documents in the dataset.
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| 7 | Total number of examples missing: 211
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| 8 | Total number of positive examples: 668
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| 9 | Deleting columns...
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| 10 | Discretizing columns...
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| 11 | Building classifier...
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| 12 |
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| 13 | Naive Bayes
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| 14 |
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| 15 | Class yes: P(C) = 0.00481649
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| 16 |
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| 17 | Attribute keyword_freq
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| 18 | '(-inf-0]' '(0-17]' '(17-18]' '(18-inf)'
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| 19 | 0.39479393 0.52711497 0.01952278 0.05856833
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| 20 |
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| 21 | Attribute tfidf
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| 22 | '(-inf-0.000347]' '(0.000347-0.00237]' '(0.00237-0.00512]' '(0.00512-0.0126]' '(0.0126-0.0474]' '(0.0474-inf)'
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| 23 | 0.00647948 0.1663067 0.22678186 0.28293737 0.24406048 0.07343413
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| 24 |
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| 25 | Attribute first_occurrence
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| 26 | '(-inf-0.00207]' '(0.00207-0.0103]' '(0.0103-0.0343]' '(0.0343-0.142]' '(0.142-inf)'
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| 27 | 0.21861472 0.20995671 0.24242424 0.19264069 0.13636364
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| 28 |
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| 29 |
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| 30 |
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| 31 | Class no: P(C) = 0.99518351
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| 32 |
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| 33 | Attribute keyword_freq
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| 34 | '(-inf-0]' '(0-17]' '(17-18]' '(18-inf)'
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| 35 | 0.86182702 0.13687325 0.00001057 0.00128916
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| 36 |
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| 37 | Attribute tfidf
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| 38 | '(-inf-0.000347]' '(0.000347-0.00237]' '(0.00237-0.00512]' '(0.00512-0.0126]' '(0.0126-0.0474]' '(0.0474-inf)'
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| 39 | 0.22192166 0.52464681 0.16605556 0.06533385 0.02027748 0.00176464
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| 40 |
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| 41 | Attribute first_occurrence
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| 42 | '(-inf-0.00207]' '(0.00207-0.0103]' '(0.0103-0.0343]' '(0.0343-0.142]' '(0.142-inf)'
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| 43 | 0.01623061 0.04124223 0.10043747 0.2244706 0.61761909
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| 44 |
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| 45 |
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| 46 | Finding most probable keyphrases...
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| 47 | Finding best cutoffs...
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| 48 | Best rank cutoff: 8 Best prob cutoff: 0.25999999999999934 F-Measure: 0.22979397781299524
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| 49 | Classifying phrases...
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| 50 | Preparing data...
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| 51 | Counting positive examples...
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| 52 | Looking for missed keyphrases in the dataset...
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| 53 | Found 500 documents in the dataset.
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| 54 | Total number of examples missing: 809
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| 55 | Total number of positive examples: 2709
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| 56 | Deleting columns...
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| 57 | Finding most probable keyphrases...
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| 58 | Computing statistics...
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| 59 | Rank cutoff: 8
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| 60 | Probability cutoff: 0.25999999999999934
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| 61 | F-Measure: 0.22598870056497175
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| 62 | Rank Prec. Conf.
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| 63 | 1 0.308 0.0406 &&&
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| 64 | 2 0.287 0.0291 &&&
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| 65 | 3 0.26 0.0237 &&&
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| 66 | 4 0.2395 0.0196 &&&
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| 67 | 5 0.2288 0.0174 &&&
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| 68 | 6 0.2177 0.0159 &&&
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| 69 | 7 0.2071 0.0143 &&&
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| 70 | 8 0.1913 0.013 &&&
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| 71 | 9 0.1791 0.0117 &&&
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| 72 | 10 0.1696 0.011 &&&
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| 73 | 11 0.1622 0.0102 &&&
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| 74 | 12 0.1567 0.0097 &&&
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| 75 | 13 0.1486 0.0091 &&&
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| 76 | 14 0.1436 0.0086 &&&
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| 77 | 15 0.1377 0.0081 &&&
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| 78 | 16 0.1325 0.0077 &&&
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| 79 | 17 0.128 0.0073 &&&
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| 80 | 18 0.1236 0.0071 &&&
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| 81 | 19 0.1195 0.0068 &&&
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| 82 | 20 0.1146 0.0065 &&&
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