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PCA
Dimensionality reduction Preprocessing Data manipulation Education Feature importance Encoding Forward feature selection T-SNE Analytics Mining
+3
  1. Workflow
    Techniques for Dimensionality Reduction
    ETL Big data Data preprocessing
    +11
    This workflow performs classification on data sets that were reduced using the following dimensionality reduction techniques: - L…
    knime > Examples > 04_Analytics > 01_Preprocessing > 02_Techniques_for_Dimensionality_Reduction > 02_Techniques_for_Dimensionality_Reduction
    1
    knime
  2. Workflow
    Statistical Market Segmentation - Questionnaire Data
    Customer Segmentation PCA
    +10
    This workflow shows how to apply a combination of two multivariate statistical techniques to solve a customer segmentation proble…
    francescots > Public > Statistics > Examples > Statistical Market Segmentation - Questionnaire Data
    1
    francescots
  3. Workflow
    Data Preprocessing for ML Models
    Preprocessing Partitioning Outlier detection
    +7
    This workflow demonstrates the following standard preprocessing steps before training a machine learning model: - Partitioning - …
    knime > Examples > 04_Analytics > 01_Preprocessing > 04_Data_Preprocessing_for_ML_Models
    1
    knime
  4. Node / Manipulator
    H2O PCA
    Analytics Integrations H2O Machine Learning
    +2
    This node applies a Principal Component Analysis (PCA) model using H2O .
    0
    knime
  5. Node / Manipulator
    H2O PCA Apply
    Analytics Integrations H2O Machine Learning
    +2
    This node applies a PCA model to reduce the dimensionality of the input dataset. Important note: all columns used for training th…
    0
    knime
  6. Node / Manipulator
    H2O PCA Compute
    Analytics Integrations H2O Machine Learning
    +2
    Compute a Principal Component Analysis (PCA) model using H2O . This model can later be used to reduce the dimensionality of a dat…
    0
    knime
  7. Node / Manipulator
    PCA Apply (deprecated)
    Analytics Mining PCA
    This node applies a projection to the principal components on the given input data. The data model of the PCA computation node ca…
    0
    knime
  8. Node / Manipulator
    PCA Apply
    Analytics Mining PCA
    +1
    This node applies a projection to the principal components on the given input data. The data model of the PCA computation node ca…
    0
    knime
  9. Node / Manipulator
    PCA
    Analytics Mining PCA
    This node performs a principal component analysis (PCA) on the given data. The input data is projected from its original feature …
    0
    knime
  10. Node / Manipulator
    PCA Compute (deprecated)
    Analytics Mining PCA
    This node performs a principal component analysis (PCA) on the given input data. The directions of maximal variance (the principa…
    0
    knime
  11. Node / Manipulator
    PCA Compute
    Analytics Mining PCA
    This node performs a principal component analysis (PCA) on the given input data. The directions of maximal variance (the principa…
    0
    knime
  12. Node / Manipulator
    PCA (deprecated)
    Analytics Mining PCA
    This node performs a principal component analysis (PCA) on the given data. The input data is projected from its original feature …
    0
    knime
  13. Node / Manipulator
    PCA Inversion
    Analytics Mining PCA
    +1
    This node inverts the transformation applied by the PCA Apply node. Given data in the space resulting from the PCA reduction are …
    0
    knime
  14. Node / Manipulator
    PCA Inversion (deprecated)
    Analytics Mining PCA
    This node inverts the transformation applied by the PCA Apply node. Given data in the space resulting from the PCA reduction is t…
    0
    knime
  15. Workflow
    Dimensionality Reduction - exercise
    Dimensionality reduction Data manipulation Preprocessing
    +3
    Introduction to Machine Learning Algorithms course - Session 4 Exercise 4 Apply the following dimensionality reduction techniques…
    hayasaka > KNIME Spring Summit Training 2023 > L4-ML Introduction to Machine Learning Algorithms > Session_4 > 01_Exercises > 04_Dimensionality_Reduction_exercise
    0
    hayasaka
  16. Workflow
    Dimensionality Reduction - exercise
    Dimensionality reduction Data manipulation Preprocessing
    +3
    Introduction to Machine Learning Algorithms course - Session 4 Exercise 4 Apply the following dimensionality reduction techniques…
    jiyeonee > Public > L4-ML Introduction to Machine Learning Algorithms > Session_4 > 01_Exercises > 04_Dimensionality_Reduction
    0
    jiyeonee
  17. Workflow
    Clustering con dati a più dimensioni utilizzando PCA
    PCA K-Means
    In questo Workflow utilizzeremo K-Means anteponendo il nodo PCA. Questo ci consentirà di 'visualizzare' i cluster creati tramite …
    falaimo > Public > ABIGAIL(M) > Customer segmentation > mall_customer(PCA)
    0
    falaimo
  18. Workflow
    Handling sparse categorial variables with Word2Vec
    Encoding Sparse data Embedding
    +3
    This workflow shows how to compute word embedding on a set of categorical variables with the granularity which allows them to be …
    francescots > Public > Statistics > Examples > Variables Encoding with word2vec
    0
    francescots
  19. Workflow
    Dimensionality Reduction - solution
    Dimensionality reduction Data manipulation Preprocessing
    +3
    Introduction to Machine Learning Algorithms course - Session 4 Solution to exercise 4 Apply the following dimensionality reductio…
    jiyeonee > Public > L4-ML Introduction to Machine Learning Algorithms > Session_4 > 02_Solutions > 04_Dimensionality_Reduction_solution
    0
    jiyeonee
  20. Workflow
    Dimensionality Reduction
    Dimensionality reduction Data manipulation Preprocessing
    +3
    Introduction to Machine Learning Algorithms course - Session 4 Solution to exercise 4 Apply the following dimensionality reductio…
    hayasaka > L4-ML-2Hrs-2021-07 > Solutions > 07_Dimensionality_Reduction_solution
    0
    hayasaka