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391 results

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Weka
Induction Knime Rule Self Associator Borgelt JRip M5 Self-Tuning Analytics
+8
  1. Go to item
    Workflow
    Machine Learning Meta Collection (with KNIME)
    Knime Machine Learning
    +11
    Machine Learning Meta Collection (with KNIME) This meta collection is about machine learning. It contains links to some examples …
    mlauber71 > Public > _machine_learning_meta_collection
    1
    mlauber71
  2. Go to item
    Workflow
    use the new (KNIME 4.5) Python Script node to read and write ARFF file into KNIME, export it again as Parquet, put it into SQLite database and read it back
    Parquet Arrow Import
    +6
    use the new (KNIME 4.5) Python Script node to read and write ARFF file into KNIME, export it again as Parquet, put it into SQLite…
    mlauber71 > Public > kn_example_python_read_arff_file
    0
    mlauber71
  3. Go to item
    Workflow
    Rule Induction with Weka M5Rules (with numeric target)
    Weka Rule Induction
    +2
    Rule Induction with Weka M5Rules WekaRules, right click on magnifying glass "View: Weka Node View" The use of the Rule finders re…
    mlauber71 > Public > kn_example_rule_induction_numeric_target
    0
    mlauber71
  4. Go to item
    Workflow
    Rule Induction with Weka Rule Nodes and Yacaree Associator
    Weka Rule Induction
    +7
    Rule Induction with Weka Rule Nodes and Yacaree Associator Weka Hot Spot Rules, right click on magnifying glass "View: Weka Node …
    mlauber71 > Public > kn_example_rule_induction_weka_hotspot_and_yacaree_rules
    0
    mlauber71
  5. Go to item
    Node / Learner
    A1DE (3.7)
    Analytics Integrations Weka
    +4
    AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…
    0
    knime
  6. Go to item
    Node / Learner
    A1DEUpdateable (3.7)
    Analytics Integrations Weka
    +4
    AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…
    0
    knime
  7. Go to item
    Node / Learner
    A2DE (3.7)
    Analytics Integrations Weka
    +4
    A2DE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…
    0
    knime
  8. Go to item
    Node / Learner
    A2DEUpdateable (3.7)
    Analytics Integrations Weka
    +4
    A2DE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…
    0
    knime
  9. Go to item
    Node / Learner
    ADTree (3.6)
    Analytics Integrations Weka
    +3
    Class for generating an alternating decision tree. The basic algorithm is based on: Freund, Y., Mason, L.: The alternating decisi…
    0
    knime
  10. Go to item
    Node / Other
    ADTree (deprecated)
    Analytics Integrations Weka
    +3
    Class for generating an alternating decision tree. For further options, click the 'More' - button in the dialog. All weka dialogs…
    0
    knime
  11. Go to item
    Node / Learner
    AODE (3.6)
    Analytics Integrations Weka
    +3
    AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that h…
    0
    knime
  12. Go to item
    Node / Other
    AODE (deprecated)
    Analytics Integrations Weka
    +3
    AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models. For f…
    0
    knime
  13. Go to item
    Node / Learner
    AODEsr (3.6)
    Analytics Integrations Weka
    +3
    AODEsr augments AODE with Subsumption Resolution.AODEsr detects specializations between two attribute values at classification ti…
    0
    knime
  14. Go to item
    Node / Learner
    AdaBoostM1 (3.6)
    Analytics Integrations Weka
    +3
    Class for boosting a nominal class classifier using the Adaboost M1 method. Only nominal class problems can be tackled. Often dra…
    0
    knime
  15. Go to item
    Node / Learner
    AdaBoostM1 (3.7)
    Analytics Integrations Weka
    +3
    Class for boosting a nominal class classifier using the Adaboost M1 method Only nominal class problems can be tackled.Often drama…
    0
    knime
  16. Go to item
    Node / Other
    AdaBoostM1 (deprecated)
    Analytics Integrations Weka
    +3
    Class for boosting a nominal class classifier using the Adaboost M1 method. For further options, click the 'More' - button in the…
    0
    knime
  17. Go to item
    Node / Learner
    AdditiveRegression (3.6)
    Analytics Integrations Weka
    +3
    Meta classifier that enhances the performance of a regression base classifier. Each iteration fits a model to the residuals left …
    0
    knime
  18. Go to item
    Node / Learner
    AdditiveRegression (3.7)
    Analytics Integrations Weka
    +3
    Meta classifier that enhances the performance of a regression base classifier Each iteration fits a model to the residuals left b…
    0
    knime
  19. Go to item
    Node / Other
    AdditiveRegression (deprecated)
    Analytics Integrations Weka
    +3
    Meta classifier that enhances the performance of a regression base classifier. For further options, click the 'More' - button in …
    0
    knime
  20. Go to item
    Node / Learner
    Apriori (3.6)
    Analytics Integrations Weka
    +2
    Class implementing an Apriori-type algorithm. Iteratively reduces the minimum support until it finds the required number of rules…
    0
    knime

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