Difference between revisions of "Página de pruebas"
Adelo Vieira (talk | contribs) (Tag: Visual edit) |
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| − | == RTextTools - A Supervised LearningPackage for Text Classification == | + | ==RTextTools - A Supervised LearningPackage for Text Classification== |
http://www.rtexttools.com/ | http://www.rtexttools.com/ | ||
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|- | |- | ||
|Support vector machine | |Support vector machine | ||
| − | |[https://cran.r-project.org/web/packages/e1071/index.html | + | |Meyer et al., 2012 |
| − | + | |[https://cran.r-project.org/web/packages/e1071/index.html e1071] | |
|SVM | |SVM | ||
|Low-memory algorithms | |Low-memory algorithms | ||
| Line 24: | Line 24: | ||
|Glmnet | |Glmnet | ||
|Friedman et al., 2010 | |Friedman et al., 2010 | ||
| − | | | + | |[https://cran.r-project.org/web/packages/glmnet/index.html glmnet] |
|GLMNET | |GLMNET | ||
|Low-memory algorithms | |Low-memory algorithms | ||
| Line 31: | Line 31: | ||
|Maximum entropy | |Maximum entropy | ||
|Jurka, 2012 | |Jurka, 2012 | ||
| − | | | + | |[https://cran.r-project.org/web/packages/maxent/index.html maxent] |
|MAXENT | |MAXENT | ||
|Low-memory algorithms | |Low-memory algorithms | ||
| Line 37: | Line 37: | ||
|- | |- | ||
|Scaled linear discriminant analysis | |Scaled linear discriminant analysis | ||
| − | | | + | |Peters and Hothorn, 2012 |
|[https://cran.r-project.org/web/packages/ipred/index.html ipred] | |[https://cran.r-project.org/web/packages/ipred/index.html ipred] | ||
|SLDA | |SLDA | ||
| Line 44: | Line 44: | ||
|- | |- | ||
|Bagging | |Bagging | ||
| − | | | + | |Peters and Hothorn, 2012 |
|[https://cran.r-project.org/web/packages/ipred/index.html ipred] | |[https://cran.r-project.org/web/packages/ipred/index.html ipred] | ||
|BAGGING | |BAGGING | ||
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|- | |- | ||
|Boosting | |Boosting | ||
| − | | | + | |Tuszynski, 2012 |
|[https://cran.r-project.org/web/packages/caTools/index.html caTools] | |[https://cran.r-project.org/web/packages/caTools/index.html caTools] | ||
|BOOSTING | |BOOSTING | ||
| Line 58: | Line 58: | ||
|- | |- | ||
|Random forest | |Random forest | ||
| − | | | + | |Liawand Wiener, 2002 |
|[https://cran.r-project.org/web/packages/randomForest/index.html randomForest] | |[https://cran.r-project.org/web/packages/randomForest/index.html randomForest] | ||
|RF | |RF | ||
Revision as of 00:26, 7 April 2019
RTextTools - A Supervised LearningPackage for Text Classification
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:
| Algorithms | Author | From package | Keyword | Comment | |
|---|---|---|---|---|---|
| Support vector machine | Meyer et al., 2012 | e1071 | SVM | Low-memory algorithms | |
| Glmnet | Friedman et al., 2010 | glmnet | GLMNET | Low-memory algorithms | |
| Maximum entropy | Jurka, 2012 | maxent | MAXENT | Low-memory algorithms | |
| Scaled linear discriminant analysis | Peters and Hothorn, 2012 | ipred | SLDA | ||
| Bagging | Peters and Hothorn, 2012 | ipred | BAGGING | ||
| Boosting | Tuszynski, 2012 | caTools | BOOSTING | ||
| Random forest | Liawand Wiener, 2002 | randomForest | RF | ||
| Neural networks | Venables and Ripley, 2002 | nnet | NNET | ||
| Classification or regression tree | Ripley., 2012 | tree | TREE |
GLMNET <- train_model(container,"GLMNET")
