Bootstrap Sampling
Samples the data using bootstrapping.
Bootstrapping is a sampling technique, which randomly draws rows from the input with replacement.
The output table will therefore likely contain duplicate rows while other rows are not present in the
output at all.
Dialog Options
- Sample size in %
-
The amount of samples relative to the original
table.
- Absolute sample size
-
The absolute amount of samples created.
- Use random seed
-
You may enter a fixed seed here in order to get
reproducible results
upon re-execution. If you do not specify a seed,
a new random seed is
taken for each execution.
- Append count of occurrences
-
Will append a column containing the number of
times, this data is present
in the bootstrap samples.
- Append original RowID
-
Will append a column containing the original RowID
in the bootstrap samples.
- RowID separator
-
The bootstrap samples have a RowID that is
composed of the original
RowID, the separator and an incremented number
for the copies of each
row.
Ports
Input Ports
0 |
Table containing the
data that should be sampled.
|
Output Ports
0 |
The extracted samples.
|
1 |
The data that has not
been used.
|
This node is contained in KNIME Base Nodes
provided by KNIME GmbH, Konstanz, Germany.