This workflow performs classification on data sets that were reduced using the following dimensionality reduction techniques:
- Linear Discriminant Analysis (LDA)
- Missing values ratio
- Low variance filter
- High correlation filter
- Ensemble tree
- Backward feature elimination
- Forward feature selection
The performances of the classification models are compared to the performance that is achieved when all columns are retained in terms of overall accuracy and AuC statistics. These evaluation metrics are produced by the best performing classification model out of this bag of models:
- Multilayer Feedforward Neural Networks
- Naive Bayes
- Decision Tree
To use this workflow in KNIME, download it from the below URL and open it in KNIME:Download Workflow
Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to firstname.lastname@example.org, follow @NodePit on Twitter, or chat on Gitter!
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