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第2行： |
| | *[[How to import the sparse data of vsm to weka]] | | *[[How to import the sparse data of vsm to weka]] |
| | | | |
| − | ==Document classification of Sougou data == | + | ==Test== |
| − | * DATA
| + | [[Sougou data]] |
| − | :* Data from SougouLab [http://www.sogou.com/labs/dl/c.html],using SogouC.reduced(30M)
| + | |
| − | :* 9-Classes:财经,IT,健康,体育,旅游,教育,招聘,文化,军事
| + | |
| − | :* train and test: train(),test(),dev()
| + | |
| − | *Text preprocessing
| + | |
| − | :* Segment word using wordlist of 9W.(tencent)
| + | |
| − | :* Remove stop word.stop_wordlist is
| + | |
| − | :*
| + | |
| − | *Some Tools
| + | |
| − | :* weka
| + | |
| − | :* scw
| + | |
| − | :* google word2ve
| + | |
| − | :* LDA
| + | |
| − | *class map
| + | |
| − | C000007 汽车
| + | |
| − | C000008 财经
| + | |
| − | C000010 IT
| + | |
| − | C000013 健康
| + | |
| − | C000014 体育
| + | |
| − | C000016 旅游
| + | |
| − | C000020 教育
| + | |
| − | C000022 招聘
| + | |
| − | C000023 文化
| + | |
| − | C000024 军事
| + | |
| − | ===VSM Test===
| + | |
| − | *Data
| + | |
| − | :* dimension:9402
| + | |
| − | *Method
| + | |
| − | :* document reprenstion: use the tf-idf weight for word weight
| + | |
| − | :* classifier: Native Bayes
| + | |
| − | *Result
| + | |
| − | | + | |
| − | {| border="2px"
| + | |
| − | |+ classification result
| + | |
| − | |-
| + | |
| − | ! !! 财经!! IT!! 健康!! 体育!! 旅游 !!教育 !! 招聘!! 文化!!军事!!sum
| + | |
| − | |-
| + | |
| − | ! ACC-test
| + | |
| − | | 0.72139 || 0.72139 || 0.75124 || 0.82089 || 0.79602 || 0.61194 || 0.70647 || 0.64179|| 0.79104 || 0.72913
| + | |
| − | |-
| + | |
| − | ! ACC-train
| + | |
| − | | 0.678 || 0.718 || 0.708 || 0.708 || 0.73
| + | |
| − | |-
| + | |
| − | |}
| + | |
| − | | + | |
| − | ===LDA Test===
| + | |
| − | ===Word2vec Test===
| + | |
| − | *Word2vec result
| + | |
| − | | + | |
| − | {| border="2px"
| + | |
| − | |+ classification result Of ACC in different dimension
| + | |
| − | |-
| + | |
| − | ! Dimension !! 财经!! IT!! 健康!! 体育!! 旅游 !!教育 !! 招聘!! 文化!!军事!!sum
| + | |
| − | |-
| + | |
| − | ! 10
| + | |
| − | | 0.766169154|| 0.383084577|| 0.52238806|| 0.820895522|| 0.666666667|| 0.44278607|| 0.567164179|| 0.721393035|| 0.850746269|| 0.637921504
| + | |
| − | |-
| + | |
| − | !20
| + | |
| − | |0.781094527 0.537313433 0.572139303 0.830845771 0.76119403 0.452736318 0.611940299 0.646766169 0.860696517 0.672747374
| + | |
| − | |-
| + | |
| − | !30
| + | |
| − | |0.815920398 0.671641791 0.606965174 0.835820896 0.766169154 0.552238806 0.577114428 0.68159204 0.885572139 0.710337203
| + | |
| − | |-
| + | |
| − | !40
| + | |
| − | |0.7960199 0.68159204 0.631840796 0.805970149 0.756218905 0.572139303 0.577114428 0.701492537 0.905472637 0.714206744
| + | |
| − | |-
| + | |
| − | !50
| + | |
| − | |0.805970149 0.691542289 0.641791045 0.800995025 0.751243781 0.552238806 0.651741294 0.656716418 0.910447761 0.718076285
| + | |
| − | |-
| + | |
| − | !60
| + | |
| − | |0.7960199 0.68159204 0.626865672 0.776119403 0.736318408 0.572139303 0.626865672 0.651741294 0.895522388 0.707020453
| + | |
| − | |-
| + | |
| − | !70
| + | |
| − | |0.7960199 0.701492537 0.621890547 0.781094527 0.771144279 0.572139303 0.631840796 0.656716418 0.905472637 0.715312327
| + | |
| − | |-
| + | |
| − | !80
| + | |
| − | |0.7960199 0.686567164 0.626865672 0.805970149 0.776119403 0.582089552 0.631840796 0.676616915 0.905472637 0.720840243
| + | |
| − | |-
| + | |
| − | !90
| + | |
| − | |0.805970149 0.71641791 0.621890547 0.776119403 0.766169154 0.572139303 0.646766169 0.666666667 0.915422886 0.720840243
| + | |
| − | |-
| + | |
| − | !100
| + | |
| − | |0.776119403 0.706467662 0.631840796 0.751243781 0.786069652 0.577114428 0.646766169 0.666666667 0.910447761 0.716970702
| + | |
| − | |-
| + | |
| − | !110
| + | |
| − | |0.771144279 0.71641791 0.656716418 0.741293532 0.76119403 0.597014925 0.606965174 0.691542289 0.910447761 0.716970702
| + | |
| − | |-
| + | |
| − | !120
| + | |
| − | |0.76119403 0.71641791 0.646766169 0.756218905 0.766169154 0.60199005 0.661691542 0.686567164 0.915422886 0.723604201
| + | |
| − | |-
| + | |
| − | !130
| + | |
| − | |0.776119403 0.731343284 0.631840796 0.76119403 0.771144279 0.577114428 0.626865672 0.701492537 0.905472637 0.720287452
| + | |
| − | |-
| + | |
| − | !140
| + | |
| − | |0.76119403 0.746268657 0.63681592 0.736318408 0.786069652 0.587064677 0.651741294 0.68159204 0.900497512 0.720840243
| + | |
| − | |-
| + | |
| − | !150
| + | |
| − | |0.756218905 0.726368159 0.63681592 0.736318408 0.771144279 0.611940299 0.651741294 0.686567164 0.910447761 0.720840243
| + | |
| − | |-
| + | |
| − | !160
| + | |
| − | |0.751243781 0.71641791 0.646766169 0.731343284 0.776119403 0.597014925 0.651741294 0.696517413 0.895522388 0.718076285
| + | |
| − | |-
| + | |
| − | !170
| + | |
| − | |0.756218905 0.741293532 0.661691542 0.731343284 0.766169154 0.60199005 0.651741294 0.666666667 0.900497512 0.71973466
| + | |
| − | |-
| + | |
| − | !180
| + | |
| − | |0.781094527 0.731343284 0.651741294 0.736318408 0.781094527 0.606965174 0.631840796 0.676616915 0.895522388 0.721393035
| + | |
| − | |-
| + | |
| − | !190
| + | |
| − | |0.771144279 0.726368159 0.661691542 0.731343284 0.766169154 0.60199005 0.631840796 0.706467662 0.900497512 0.721945826
| + | |
| − | |-
| + | |
| − | !200
| + | |
| − | |0.771144279 0.736318408 0.641791045 0.706467662 0.771144279 0.606965174 0.611940299 0.71641791 0.900497512 0.718076285
| + | |
| − | |-
| + | |
| − | |}
| + | |
