Back to Adaptive Vision Studio website
You are here: Start » Filter Reference » Data Classification » Principal Component Analysis » NormalizeMatrixData
Expert| Module: | FoundationPro |
|---|
Treats Matrix as a data frame, where examples are in rows while columns represent features, and normalizes the data by subtracting mean from each column and dividing it by its standard deviation.
| Name | Type | Description | |
|---|---|---|---|
 |
inMatrix | Matrix | Input data frame. |
|
inMeansVector | Matrix* | If provided, will be used in normalization of inMatrix. |
|
inStandardDeviationsVector | Matrix* | If provided, will be used in normalization of inMatrix. |
 |
outNormalizedMatrix | Matrix | Resulting normalized matrix. |
|
outMeansVector | Matrix | Resulting Means vector - copy of inMeansVector, or calculated Means, if inMeansVector was set NIL. |
|
outStandardDeviationsVector | Matrix | Resulting StdDevs vector - copy of inStandardDeviationsVector, or calculated Means, if inStandardDeviationsVector was set NIL. |
Errors
This filter can throw an exception to report error. Read how to deal with errors in Error Handling.
List of possible exceptions:
| Error type | Description |
|---|---|
| DomainError | Incorrect matrix dimensions in NormalizeData. |
| DomainError | One can provide both Means and StdDevs vector or none of them. |
Complexity Level
This filter is available on Expert Complexity Level.
