The fuzzy c-means algorithm is a well-known unsupervised learning technique that can be used to
reveal the underlying structure of the data. Fuzzy clustering allows each data point to belong to
several clusters, with a degree of membership to each one.
Make sure that the input data is
normalized to obtain better clustering results.
The first output datatable provides the
original datatable with the cluster memberships to each cluster.
The second datatable provides the values of the cluster prototypes.
Additionally, it is possible to induce a noise cluster, to detect noise in the
dataset, based on the approach from R. N. Dave: 'Characterization and detection of noise in clustering'.
Options
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Linear Correlation2 %- Interactive Table (legacy)2 %
XLS Writer2 %- Table Partitioner1 %
- Pivot1 %
- Decision Tree Predictor1 %
- Silhouette Coefficient1 %
- String Replacer1 %
Naive Bayes Learner< 1 %Column Appender< 1 %PMML Predictor< 1 %- Color Manager< 1 %
- 3D Scatter Plot (Plotly)< 1 %
- Cluster Assigner< 1 %
- Fuzzy c-Means< 1 %
Auto-Binner< 1 %- Denormalizer< 1 %
- Value Counter< 1 %
- Box Plot (legacy)< 1 %
- 2D/3D Scatterplot< 1 %
- Fuzzy Rule Learner< 1 %
- Hierarchical Cluster Assigner (local)< 1 %
- PCA Compute< 1 %
- Column Aggregator< 1 %
- RowID< 1 %
Column Splitter< 1 %- One-way ANOVA< 1 %
- Lift Chart (legacy)< 1 %
- Scatter Plot (legacy)< 1 %
- Distance Matrix Calculate< 1 %
- Similarity Search< 1 %
- PMML to Cell< 1 %
- Pie Chart (JFreeChart)< 1 %
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- Rule Viewer (local) (Legacy)< 1 %
- CSV Writer< 1 %
Model Writer< 1 %- Naive Bayes Predictor< 1 %
- Hierarchical Clustering< 1 %
- Hierarchical Cluster View< 1 %
k-Means (deprecated)< 1 %- DBSCAN< 1 %
- MultiLayerPerceptron Predictor< 1 %
- Linear Regression Learner< 1 %
- Scorer< 1 %
- Entropy Scorer< 1 %
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- PCA< 1 %
- Concatenate< 1 %
- Column Renamer< 1 %
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Row Filter (deprecated)< 1 %- GroupBy< 1 %
Joiner< 1 %- Joiner< 1 %
- Denormalizer (PMML)< 1 %
Column Rename< 1 %- Row Sampler< 1 %
- String Manipulation< 1 %
- Unpivot< 1 %
- Rule Engine< 1 %
- Crosstab< 1 %
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Excel Writer (XLS)< 1 %- Excel Writer< 1 %
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Cell Replacer< 1 %String To Number< 1 %- Column Appender< 1 %
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- R View (Table)< 1 %
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Table Writer< 1 %Loop End (2 ports)< 1 %- X-Partitioner< 1 %
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K Nearest Neighbor< 1 %PCA Apply< 1 %- Numeric Scorer< 1 %
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Excel Sheet Appender (XLS)< 1 %- Spark Line Appender< 1 %
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- Column Selection (legacy)< 1 %
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- R Snippet< 1 %
- Type< 1 %
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- Variable to Table Column< 1 %
Image Writer (Table Column)< 1 %- ARFF Writer< 1 %
CSV Writer< 1 %- Model Writer< 1 %
- Feature Selection Filter< 1 %
- Feature Selection Loop Start (2:2)< 1 %
- Loop End (Column Append)< 1 %
Loop End< 1 %- Group Loop Start< 1 %
- X-Aggregator< 1 %
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- PNN Predictor< 1 %
- Hierarchical Clustering (DistMatrix)< 1 %
- Decision Tree Learner< 1 %
- K Nearest Neighbor< 1 %
- MDS< 1 %
PCA Compute< 1 %PCA< 1 %Logistic Regression Learner< 1 %- Logistic Regression Predictor< 1 %
Regression Predictor< 1 %- SVM Predictor< 1 %
- PCA Apply< 1 %
Gradient Boosted Trees Learner (Regression)< 1 %Tree Ensemble Learner< 1 %- Tree Ensemble Learner< 1 %
Tree Ensemble Predictor< 1 %Random Forest Learner< 1 %- Random Forest Learner (Regression)< 1 %
- Random Forest Predictor< 1 %
- Constant Value Row Appender< 1 %
- Binner (Dictionary)< 1 %
- Cell Splitter< 1 %
- Column Combiner< 1 %
- Category to Number< 1 %
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Number To String< 1 %- String to Number< 1 %
- Lag Column< 1 %
Constant Value Column< 1 %- Linear Correlation< 1 %
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- Filter Apply< 1 %
- Nominal Value Row Filter< 1 %
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- Column Filter (PMML)< 1 %
- Many to One (PMML)< 1 %
Number To String (PMML)< 1 %String To Number (PMML)< 1 %- Sorter< 1 %
- Table Transposer< 1 %
- Ruleset Editor< 1 %
- Cronbach Alpha< 1 %
- Data Explorer< 1 %
- Kruskal-Wallis Test< 1 %
- Wilcoxon-Mann-Whitney Test< 1 %
- Statistics< 1 %
CASE Switch Data (End)< 1 %- Extract Table Dimension< 1 %
- Conditional Box Plot (legacy)< 1 %
- Enrichment Plotter (legacy)< 1 %
- HiLite Table (legacy)< 1 %
- Histogram (legacy)< 1 %
- Pie chart (legacy)< 1 %
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- SDF Writer< 1 %
DB Writer< 1 %- Mahalanobis Distance< 1 %
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PMML Ensemble Predictor< 1 %- PMML Ensemble to Table< 1 %
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- HeatMap (JFreeChart)< 1 %
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XLS Sheet Appender< 1 %Excel Writer (XLS)< 1 %Stanford tagger< 1 %- Bag Of Words Creator< 1 %
- Tag Cloud< 1 %
- Weka Cluster Assigner (3.7)< 1 %
- Nominal Row Filter Configuration< 1 %
- Heatmap (JavaScript) (legacy)< 1 %
- ROC Curve (JavaScript) (legacy)< 1 %
- Image Normalizer< 1 %
Python Script (1⇒1)< 1 %- Text Classifier Learner< 1 %
Views
- Statistics View
- Shows the WithinClusterVariation and the BetweenClusterVariation, which are indicators for 'good' clustering.
Workflows
ClusterKNIME Hub- Clustering_RetrievalKNIME Hub
- Clustering_RetrievalKNIME Hub
- Clustering_RetrievalKNIME Hub
- Extract Fuzzy ClustersKNIME Hub
- Show all 8 workflows
Links
- No links available
Developers
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