Statements (50)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:convolutional_neural_network
unsupervised learning algorithm |
| gptkbp:alsoKnownAs |
gptkb:Kohonen_map
SOM |
| gptkbp:application |
speech recognition
bioinformatics image analysis anomaly detection market segmentation |
| gptkbp:category |
gptkb:artificial_intelligence
gptkb:machine_learning pattern recognition data mining |
| gptkbp:citation |
gptkb:IEEE_Transactions_on_Neural_Networks
Self-Organizing Maps (book by Teuvo Kohonen) |
| gptkbp:feature |
neighborhood function
topology preservation weight adaptation |
| https://www.w3.org/2000/01/rdf-schema#label |
Self-Organizing Maps
|
| gptkbp:influencedBy |
biological neural networks
|
| gptkbp:input |
high-dimensional data
|
| gptkbp:introducedIn |
1982
|
| gptkbp:inventedBy |
gptkb:Teuvo_Kohonen
|
| gptkbp:limitation |
gptkb:curse_of_dimensionality
parameter sensitivity interpretability for large maps |
| gptkbp:openSource |
gptkb:SOM_Toolbox
gptkb:MiniSom gptkb:SOMPY Kohonen package (R) |
| gptkbp:output |
low-dimensional grid
|
| gptkbp:parameter |
learning rate
number of iterations grid size neighborhood radius |
| gptkbp:relatedTo |
gptkb:principal_component_analysis
clustering algorithms vector quantization |
| gptkbp:supportsAlgorithm |
competitive learning
|
| gptkbp:trainer |
unsupervised learning
|
| gptkbp:trainingStep |
winner-takes-all
neighborhood update weight adjustment |
| gptkbp:usedFor |
gptkb:data_visualization
clustering dimensionality reduction |
| gptkbp:visualizes |
gptkb:U-matrix
component planes |
| gptkbp:bfsParent |
gptkb:SOMPY
|
| gptkbp:bfsLayer |
7
|