|
|
| (738 intermediate revisions by the same user not shown) |
| Line 1: |
Line 1: |
| − | ==RTextTools - A Supervised LearningPackage for Text Classification==
| |
| − | https://journal.r-project.org/archive/2013/RJ-2013-001/RJ-2013-001.pdf
| |
| | | | |
| − | http://www.rtexttools.com/
| |
| − |
| |
| − | https://cran.r-project.org/web/packages/RTextTools/index.html
| |
| − |
| |
| − |
| |
| − | The '''''train_model()''''' function takes each algorithm, one by one, to produce an object passable to '''''classify_model().'''''
| |
| − |
| |
| − |
| |
| − | A convenience '''''train_models()''''' function trains all models at once by passing in a vector of model requests. The syntax below demonstrates model creation for all nine algorithms:
| |
| − | {| class="wikitable"
| |
| − | |+
| |
| − | ! rowspan="2" |Algorithms
| |
| − | ! rowspan="2" |Author
| |
| − | ! rowspan="2" |From package
| |
| − | ! rowspan="2" |Keyword
| |
| − | ! colspan="2" |Accuracy
| |
| − | |-
| |
| − | !Fake news dataset
| |
| − | !Fake news challenge dataset
| |
| − | |-
| |
| − | |General linearized models
| |
| − | |Friedman et al., 2010
| |
| − | |[https://cran.r-project.org/web/packages/glmnet/index.html glmnet]
| |
| − | |GLMNET*
| |
| − | |
| |
| − | |
| |
| − | |-
| |
| − | |Support vector machine
| |
| − | |Meyer et al., 2012
| |
| − | |[https://cran.r-project.org/web/packages/e1071/index.html e1071]
| |
| − | |SVM*
| |
| − | |
| |
| − | |
| |
| − | |-
| |
| − | |Maximum entropy
| |
| − | |Jurka, 2012
| |
| − | |[https://cran.r-project.org/web/packages/maxent/index.html maxent]
| |
| − | |MAXENT*
| |
| − | |
| |
| − | |
| |
| − | |-
| |
| − | |Classification or regression tree
| |
| − | |Ripley., 2012
| |
| − | |[https://cran.r-project.org/web/packages/tree/index.html tree]
| |
| − | |TREE
| |
| − | |
| |
| − | |
| |
| − | |-
| |
| − | |Random forest
| |
| − | |Liawand Wiener, 2002
| |
| − | |[https://cran.r-project.org/web/packages/randomForest/index.html randomForest]
| |
| − | |RF
| |
| − | |
| |
| − | |
| |
| − | |-
| |
| − | |Boosting
| |
| − | |Tuszynski, 2012
| |
| − | |[https://cran.r-project.org/web/packages/caTools/index.html caTools]
| |
| − | |BOOSTING
| |
| − | |
| |
| − | |
| |
| − | |-
| |
| − | |Neural networks
| |
| − | |Venables and Ripley, 2002
| |
| − | |[https://cran.r-project.org/web/packages/nnet/index.html nnet]
| |
| − | |NNET
| |
| − | |
| |
| − | |
| |
| − | |-
| |
| − | |Bagging
| |
| − | |Peters and Hothorn, 2012
| |
| − | |[https://cran.r-project.org/web/packages/ipred/index.html ipred]
| |
| − | |BAGGING**
| |
| − | |
| |
| − | |
| |
| − | |-
| |
| − | |Scaled linear discriminant analysis
| |
| − | |Peters and Hothorn, 2012
| |
| − | |[https://cran.r-project.org/web/packages/ipred/index.html ipred]
| |
| − | |SLDA**
| |
| − | |
| |
| − | |
| |
| − | |-
| |
| − | | colspan="6" |* Low-memory algorithm
| |
| − | <nowiki>**</nowiki> Very high-memory algorithm
| |
| − | |}
| |
| − |
| |
| − |
| |
| − | GLMNET <- train_model(container,"GLMNET")
| |
| − |
| |
| − | <br />
| |
