MDS

This node maps data of a high dimensional space onto a lower (usually 2 or 3) dimensional space. Therefore the Sammons mapping is applied, which iteratively decreases the difference of the distances of high and low dimensional data. Each original data point is represented by a data point of a lower dimension. The Sammons mapping tries to keep the distance information of the high dimensional data by adjusting the low dimensional data points in a certain way. Each low dimensional data point is moved around a bit towards or back from the other points accordant to its high dimensional distances. This procedure is repeated a specified number of epochs or iterations respectively.

Options

Epochs

Specifies the number of epochs to train.

Output dimensions

Specifies the dimension of the mapped output data.

Learning rate

Specifies the learning rate to use. The learning rate is decreased automatically over the trained epochs.

Random seed

Specifies the random seed to use, which allows to reproduce a mapping even if the initialization is done randomly.

Distance metric

Select the distance metric to use for computing distances between data points.

• Euclidean: The straight-line distance between two points in n-dimensional space (L2 norm).
• Manhattan: The sum of absolute differences between coordinates (L1 norm).

Use all rows

If enabled, all rows in the input table will be used for the MDS computation. If disabled, only the specified number of rows will be used.

Number of rows to use

Specifies the number of rows to apply the MDS on.

Always include all columns

If checked, node behaves as if all columns were moved to the "Include" list.

Columns to project

Specifies the columns to use by the mapping.

Views

This node has no views

Workflows

• 00_Topic_Modeling_with_Verified_ComponentsKNIME Hub
• 00_Topic_Modeling_with_Verified_ComponentsKNIME Hub
• 03_Topic_Explorer_ExampleKNIME Hub
• 06_Topic_Modeling_LDA_Data_AppKNIME Hub
• 07_Topic_Modeling_STM_Data_AppKNIME Hub
• Activity 3.1 Topic Model Evaluation Topic ScorerKNIME Hub
• C20KNIME Hub
• dimension_reductionKNIME Hub
• JKISeasor2-20_tomljh_ver1KNIME Hub
• Justknimeit-S2C20KNIME Hub
• LDA, CTM and STMKNIME Hub
• Topic Explorer ViewKNIME Hub
• Topic Explorer ViewKNIME Hub
• Topic Explorer ViewKNIME Hub
• Topic Explorer ViewKNIME Hub
• Topic Model EvalautionKNIME Hub

Links

• No links available

Developers