FME Transformers: 2024.1
FME Transformers: 2024.1
Classifier
Sorts and groups features into a number of classes based on an attribute value, storing their class ID in a specified output attribute.
Usage Notes
-
A FeatureColorSetter using the Gradient color scheme can be used to visualize the class IDs in the style of a choropleth map.
Configuration
Input Ports
Input
Features with a numeric attribute to perform classification on.
Output Ports
Output
Features with class ID values added as specified in parameters.
<Rejected>
Features will be output through this port if their classification value is not a finite number.
Rejected Feature Handling: can be set to either terminate the translation or continue running when it encounters a rejected feature. This setting is available both as a default FME option and as a workspace parameter.
Parameters
Group Processing
Group By |
The default behavior is to use the entire set of input features as the group. This option allows you to select attributes that define which groups to form – each set of features that have the same value for all of these attributes will be processed as an independent group. |
||||
Complete Groups
|
Select the point in processing at which groups are processed:
Considerations for Using Group By
There are two typical reasons for using When Group Changes (Advanced) . The first is incoming data that is intended to be processed in groups (and is already so ordered). In this case, the structure dictates Group By usage - not performance considerations. The second possible reason is potential performance gains. Performance gains are most likely when the data is already sorted (or read using a SQL ORDER BY statement) since less work is required of FME. If the data needs ordering, it can be sorted in the workspace (though the added processing overhead may negate any gains). Sorting becomes more difficult according to the number of data streams. Multiple streams of data could be almost impossible to sort into the correct order, since all features matching a Group By value need to arrive before any features (of any feature type or dataset) belonging to the next group. In this case, using Group By with When All Features Received may be the equivalent and simpler approach. Note Multiple feature types and features from multiple datasets will not generally naturally occur in the correct order.
As with many scenarios, testing different approaches in your workspace with your data is the only definitive way to identify performance gains. |
General
Classification Value |
The value to classify features by, which must be a finite number. This value should vary across features. |
Classification Method |
The method or scheme used to determine the boundary between classes.
|
Number of Classes |
The desired number of classes to separate features into. If Classification Method is Natural Breaks and the number of classes exceeds the number of features, the maximum number of classes will be reduced to the number of features. If Classification Method is Quantile or Equal Intervals and the number of classes exceeds the number of features, some classes will be empty. |
Output Attribute Name
Class |
Name the attribute to contain the feature’s class ID, beginning with 0. |
Editing Transformer Parameters
Transformer parameters can be set by directly entering values, using expressions, or referencing other elements in the workspace such as attribute values or user parameters. Various editors and context menus are available to assist. To see what is available, click beside the applicable parameter.
How to Set Parameter Values
Defining Values
There are several ways to define a value for use in a Transformer. The simplest is to simply type in a value or string, which can include functions of various types such as attribute references, math and string functions, and workspace parameters.
Using the Text Editor
The Text Editor provides a convenient way to construct text strings (including regular expressions) from various data sources, such as attributes, parameters, and constants, where the result is used directly inside a parameter.
Using the Arithmetic Editor
The Arithmetic Editor provides a convenient way to construct math expressions from various data sources, such as attributes, parameters, and feature functions, where the result is used directly inside a parameter.
Conditional Values
Set values depending on one or more test conditions that either pass or fail.
Parameter Condition Definition Dialog
Content
Expressions and strings can include a number of functions, characters, parameters, and more.
When setting values - whether entered directly in a parameter or constructed using one of the editors - strings and expressions containing String, Math, Date/Time or FME Feature Functions will have those functions evaluated. Therefore, the names of these functions (in the form @<function_name>) should not be used as literal string values.
Content Types
These functions manipulate and format strings. | |
Special Characters |
A set of control characters is available in the Text Editor. |
Math functions are available in both editors. | |
Date/Time Functions | Date and time functions are available in the Text Editor. |
These operators are available in the Arithmetic Editor. | |
These return primarily feature-specific values. | |
FME and workspace-specific parameters may be used. | |
Creating and Modifying User Parameters | Create your own editable parameters. |
Dialog Options - Tables
Table Tools
Transformers with table-style parameters have additional tools for populating and manipulating values.
Row Reordering
|
Enabled once you have clicked on a row item. Choices include:
|
Cut, Copy, and Paste
|
Enabled once you have clicked on a row item. Choices include:
Cut, copy, and paste may be used within a transformer, or between transformers. |
Filter
|
Start typing a string, and the matrix will only display rows matching those characters. Searches all columns. This only affects the display of attributes within the transformer - it does not alter which attributes are output. |
Import
|
Import populates the table with a set of new attributes read from a dataset. Specific application varies between transformers. |
Reset/Refresh
|
Generally resets the table to its initial state, and may provide additional options to remove invalid entries. Behavior varies between transformers. |
Note: Not all tools are available in all transformers.
For more information, see Transformer Parameter Menu Options.
Reference
Processing Behavior |
|
Feature Holding |
Yes |
Dependencies | None |
Aliases | |
History |
FME Community
The FME Community is the place for demos, how-tos, articles, FAQs, and more. Get answers to your questions, learn from other users, and suggest, vote, and comment on new features.
Search for all results about the Classifier on the FME Community.
Examples may contain information licensed under the Open Government Licence – Vancouver, Open Government Licence - British Columbia, and/or Open Government Licence – Canada.