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
Popular Predecessors
File Reader14 %CSV Reader11 %Excel Reader (XLS)9 %Database Reader2 %XLS Reader2 %String To Number2 %PCA2 %Excel Reader (XLS)2 %- File Reader2 %
- Missing Value1 %
- Cluster Assigner1 %
Number To String1 %Table Row To Variable Loop Start1 %- Scatter Plot (legacy)1 %
Scorer< 1 %- RowID< 1 %
- GroupBy< 1 %
Column Rename< 1 %Interval Loop Start< 1 %Row Filter (deprecated)< 1 %- Fuzzy Rule Learner< 1 %
- DB Query Reader< 1 %
- k-Medoids< 1 %
- Association Rule Learner (Borgelt)< 1 %
- Fuzzy c-Means< 1 %
- Pivot< 1 %
- String to Number< 1 %
- Math Formula (Variable)< 1 %
Auto-Binner< 1 %- One to Many< 1 %
- Missing Value Column Filter< 1 %
- Normalizer< 1 %
- Table Partitioner< 1 %
Column Splitter< 1 %- Rule-based Row Splitter< 1 %
- Math Formula< 1 %
String to Date&Time< 1 %Table Row to Variable< 1 %- PCA< 1 %
- Number to String< 1 %
- Normalizer (Apply)< 1 %
- Crosstab< 1 %
- Table Row to Variable< 1 %
- Table View (JavaScript) (legacy)< 1 %
- Hierarchical Clustering< 1 %
k-Means (deprecated)< 1 %- DBSCAN< 1 %
PCA Apply< 1 %- Numeric Binner< 1 %
- Category to Number< 1 %
- Column Filter< 1 %
- Reference Column Filter< 1 %
- Normalizer (PMML)< 1 %
- Rule-based Row Filter< 1 %
- Rule Engine< 1 %
Rank Correlation< 1 %- Color Manager< 1 %
- R Snippet< 1 %
- X-Partitioner< 1 %
- PCA Apply< 1 %
- Scatter Plot (JavaScript) (legacy)< 1 %
- RDKit Descriptor Calculation< 1 %
- CSV Reader< 1 %
- Silhouette Coefficient< 1 %
- Joiner< 1 %
- Excel Reader< 1 %
- Python Script (legacy)< 1 %
Loop End (2 ports)< 1 %- Domain Calculator< 1 %
- Distance Matrix Calculate< 1 %
- Term Vector< 1 %
- Naive Bayes Predictor< 1 %
- Column Combiner< 1 %
- ARFF Reader< 1 %
- Table Creator< 1 %
Linear Correlation< 1 %- Low Variance Filter< 1 %
- TF< 1 %
Document vector< 1 %Line Reader< 1 %- Java Edit Variable< 1 %
- K Nearest Neighbor< 1 %
- Perl Scripting< 1 %
- HiLite Row Splitter< 1 %
- Denormalizer< 1 %
- DB Reader< 1 %
- Distance Matrix Reader< 1 %
- Create File/Folder Variables< 1 %
- Outlier Removal< 1 %
Table Reader< 1 %- Chunk Loop Start< 1 %
Generic Loop Start< 1 %- Association Rule Learner< 1 %
- Create Bit Vector< 1 %
Column Appender< 1 %- Column Name Replacer< 1 %
- Reference Row Filter< 1 %
- Row Sampler< 1 %
- String Manipulation< 1 %
- Timer Info< 1 %
- Spark Entropy Scorer< 1 %
- Similarity Search< 1 %
Read XLS Sheet Names< 1 %- Keygraph Keyword Extractor< 1 %
- JPMML Classifier< 1 %
- Time Difference (legacy)< 1 %
- Moving Aggregator< 1 %
- Fingerprints Expander< 1 %
Table Row to Variable< 1 %- Fuzzy Rule Predictor< 1 %
- Nominal Value Row Splitter< 1 %
Number To String (PMML)< 1 %- Rank< 1 %
- Numeric Row Splitter< 1 %
- Shuffle< 1 %
- Extract Table Dimension< 1 %
Excel Reader (XLS)< 1 %Read Excel Sheet Names (XLS)< 1 %- Spark Line Appender< 1 %
- String Configuration< 1 %
- Value Filter (legacy)< 1 %
- R Source (Table)< 1 %
- Latitude/Longitude to Coordinate< 1 %
- Column Resorter< 1 %
- End IF< 1 %
- Document Vector< 1 %
- Split Collection Column< 1 %
Database Connection Table Reader< 1 %- Java Snippet< 1 %
Counting Loop Start< 1 %- Hierarchical Cluster Assigner (local)< 1 %
K Nearest Neighbor< 1 %- Constant Value Row Appender< 1 %
Concatenate (Optional in)< 1 %Cell Splitter< 1 %- Correlation Filter< 1 %
- Double to Integer< 1 %
Row Splitter (deprecated)< 1 %Joiner< 1 %- Normalizer Apply (PMML)< 1 %
- Table Transposer< 1 %
- Statistics< 1 %
- Data Generator< 1 %
- H2O to Table< 1 %
- Java Snippet (simple)< 1 %
- Java Edit Variable (simple)< 1 %
- String Matcher< 1 %
Bag of Words Creator< 1 %- Document Data Extractor< 1 %
- Parameter Optimization Loop Start< 1 %
Python Script (1⇒1)< 1 %- RDKit MCS< 1 %
- RDKit Fingerprint< 1 %
- Normalize Plates (Z-Score)< 1 %
Active Learn Loop Start< 1 %- Extract Variables (Data)< 1 %
- Feature Selection Loop Start (1:1)< 1 %
- Loop End (Column Append)< 1 %
- Group Loop Start< 1 %
Naive Bayes Learner< 1 %- Naive Bayes Learner< 1 %
- Hierarchical Cluster Assigner< 1 %
- Decision Tree Predictor< 1 %
- MultiLayerPerceptron Predictor< 1 %
- Entropy Scorer< 1 %
- SMOTE< 1 %
- SOTA Learner< 1 %
- Random Forest Predictor (Regression)< 1 %
- Concatenate< 1 %
- Expand Bit Vector< 1 %
- Create Byte Vector< 1 %
Cell Replacer< 1 %- Cell Splitter By Position< 1 %
- Column Auto Type Cast< 1 %
- Column Aggregator< 1 %
- Many to One< 1 %
- Cross Joiner< 1 %
- Filter Apply< 1 %
- Nominal Value Row Filter< 1 %
- One to Many (PMML)< 1 %
String To Number (PMML)< 1 %- String Replacer< 1 %
- Top k Row Filter< 1 %
- Ungroup< 1 %
- Value Counter< 1 %
- Numeric Outliers< 1 %
- IF Switch< 1 %
- HiLite Table (legacy)< 1 %
- Box Plot (legacy)< 1 %
Color Appender< 1 %- Numeric Distances< 1 %
K Nearest Neighbor (Distance Function)< 1 %- Keras Network Executor< 1 %
- Universe Marker< 1 %
- Math Formula (Multi Column)< 1 %
- Geo-Coordinate Row Filter< 1 %
- Strings to Document< 1 %
- String to Term< 1 %
- t-SNE (L. Jonsson)< 1 %
- Weka Cluster Assigner (3.7)< 1 %
- Tag Cloud (JavaScript) (legacy)< 1 %
- JSON to Table< 1 %
- Python Source (legacy)< 1 %
- GET Request< 1 %
Date&Time to String< 1 %- Window Loop Start< 1 %
- Date Field Extractor (legacy)< 1 %
XML Reader< 1 %- Fingerprints< 1 %
- Table Column to Variable< 1 %
- Table Reader< 1 %
- Table Row to Variable Loop Start< 1 %
- Column Name Extractor< 1 %
- Duplicate Row Filter< 1 %
- Denormalizer (PMML)< 1 %
- Number to String (PMML)< 1 %
- Number Rounder< 1 %
- Rank Correlation< 1 %
- Data Explorer< 1 %
- Topic Extractor (Parallel LDA)< 1 %
- Category to Class< 1 %
- Table Editor (JavaScript) (legacy)< 1 %
- Integer Widget< 1 %
Extract Date&Time Fields< 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
You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.