Hub

391 results

Filter
Weka
Induction Knime Rule Self Associator
+13
  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. Node / Learner
    FilteredAssociator (3.6)
    Analytics Integrations Weka
    +2
    Class for running an arbitrary associator on data that has been passed through an arbitrary filter. Like the associator, the stru…
    0
  7. Node / Learner
    FPGrowth (3.6)
    Analytics Integrations Weka
    +2
    Class implementing the FP-growth algorithm for finding large item sets without candidate generation. Iteratively reduces the mini…
    0
  8. Node / Learner
    GeneralizedSequentialPatterns (3.6)
    Analytics Integrations Weka
    +2
    Class implementing a GSP algorithm for discovering sequential patterns in a sequential data set. The attribute identifying the di…
    0
  9. Node / Learner
    PredictiveApriori (3.6)
    Analytics Integrations Weka
    +2
    Class implementing the predictive apriori algorithm to mine association rules. It searches with an increasing support threshold f…
    0
  10. Node / Learner
    Tertius (3.6)
    Analytics Integrations Weka
    +2
    Finds rules according to confirmation measure (Tertius-type algorithm). For more information see: P. A. Flach, N. Lachiche (1999)…
    0
  11. 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
  12. 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
  13. Node / Learner
    Decorate (3.6)
    Analytics Integrations Weka
    +3
    DECORATE is a meta-learner for building diverse ensembles of classifiers by using specially constructed artificial training examp…
    0
  14. Node / Learner
    END (3.6)
    Analytics Integrations Weka
    +3
    A meta classifier for handling multi-class datasets with 2-class classifiers by building an ensemble of nested dichotomies. For m…
    0
  15. Node / Learner
    FilteredClassifier (3.6)
    Analytics Integrations Weka
    +3
    Class for running an arbitrary classifier on data that has been passed through an arbitrary filter. Like the classifier, the stru…
    0
  16. Node / Learner
    Grading (3.6)
    Analytics Integrations Weka
    +3
    Implements Grading. The base classifiers are "graded". For more information, see A.K. Seewald, J. Fuernkranz: An Evaluation of Gr…
    0
  17. Node / Learner
    GridSearch (3.6)
    Analytics Integrations Weka
    +3
    Performs a grid search of parameter pairs for the a classifier (Y-axis, default is LinearRegression with the "Ridge" parameter) a…
    0
  18. Node / Learner
    LogitBoost (3.6)
    Analytics Integrations Weka
    +3
    Class for performing additive logistic regression. This class performs classification using a regression scheme as the base learn…
    0
  19. Node / Learner
    MetaCost (3.6)
    Analytics Integrations Weka
    +3
    This metaclassifier makes its base classifier cost-sensitive using the method specified in Pedro Domingos: MetaCost: A general me…
    0
  20. Node / Learner
    MultiBoostAB (3.6)
    Analytics Integrations Weka
    +3
    Class for boosting a classifier using the MultiBoosting method. MultiBoosting is an extension to the highly successful AdaBoost t…
    0