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PCA
Dimensionality reduction Preprocessing Data manipulation Education Feature importance
+8
  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
  2. 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
  3. Workflow
    2-D Projection of Clustered Data
    K-means Pca
    This workflow uses a custom component to cluster and visualize three datasets (Sensor, Marketing Analytics, Bag of Words) in 2D. …
    rroheet > Public > Knime_Challenge_Workflow
    0
  4. Workflow
    Dimensionality Reduction
    Dimensionality reduction Data manipulation Preprocessing
    +3
    Introduction to Machine Learning Algorithms course - Session 4 Exercise 4 Apply the following dimensionality reduction techniques…
    hayasaka > L4-ML-2Hrs-2021-07 > Exercises > 07_Dimensionality_Reduction
    0
  5. Workflow
    Cluster Visualization Workflow
    K-means Pca Silhouette score
    +1
    This workflow illustrates how to use Cluster Visualization Component to perform Clustering on the data you want to analyze and vi…
    yamaceay > Public > Beginner Guide for Cluster Visualization
    0
  6. 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 > Variables Encoding with word2vec
    0
  7. 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…
    knime > Education > Courses > L4-ML Introduction to Machine Learning Algorithms > Session_4 > 02_Solutions > 04_Dimensionality_Reduction_solution
    0
  8. 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 > Statistical Market Segmentation - Questionnaire Data
    0
  9. 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
  10. 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 > Categorical Variables Encoding with word2vec
    0
  11. Workflow
    Interactive visualization of phenotypic features in zebrafish
    PCA Screening Zebrafish
    +3
    This workflow allows to explore some features from a toxicity screening in zebrafish larvae. There are 10 morphological features …
    l.thomas > Public > InteractiveFeatureExploration
    0
  12. Workflow
    Dimensionality Reduction with PCA and t-SNE
    TheGuideBook Scatter plot PCA
    +4
    This workflow applyes two dimensionality reduction techniques: -PCA -t-SNE to reduce the dataset dimensions from three to two fea…
    knime > Academic Alliance > Guide to Intelligent Data Science > Example Workflows > Chapter4 > 02_PCA_t-SNE
    0
  13. 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…
    dg-clarkston > Public > dimension_reduction_techniques
    0
  14. Workflow
    Dimensionality Reduction
    Dimensionality reduction Data manipulation Preprocessing
    +3
    Introduction to Machine Learning Algorithms course - Session 4 Exercise 4 Apply the following dimensionality reduction techniques…
    knime > Education > Courses > L4-ML Introduction to Machine Learning Algorithms > Session_4 > 01_Exercises > 04_Dimensionality_Reduction
    0
  15. Node / Manipulator
    H2O PCA
    Analytics Integrations H2O Machine Learning
    +2
    This node applies a Principal Component Analysis (PCA) model using H2O .
    0
  16. 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
  17. 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
  18. 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
  19. 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
  20. 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