ENM Maxent workflow used for optimization

Created: 2013-08-09 15:59:47 Last updated: 2013-09-04 07:19:51

Download Workflow

This workflow was used for the optimization of the Maxent algorithm from the openModeller toolbox (http://openmodeller.sourceforge.net/). The workflow uses 10-fold cross-validation and then calculates the average AUC, which can be used as fitness value during parameter optimization.

Preview

Download as scalable diagram (SVG)

Run

Run this Workflow in the Taverna Workbench...

Option 1:

Copy and paste this link into File > 'Open workflow location...'
http://www.myexperiment.org/workflows/3679/download?version=1
[ More Info Expand ]

Workflow Components

Authors (1)

Titles (1)

Descriptions (1)

Dependencies (0)

Inputs (13)

Name	Description
input_points	This input takes a text file containing species occurrence points. The file must be formatted according to the Darwin Core archive standard: each line corresponds to a different record, values are separated by comma, and the first line must be a header (also separated by comma) containing the Darwin Core terms for each column. The following terms are mandatory to run this workflow: occurrenceID, nameComplete, decimalLongitude and decimalLatitude. Only records for the first species will be used.
MinSamplesForProductThreshold	Number of samples at which product and threshold features start being used (only when auto features is enabled).
AutoFeatures	Enable auto features (0=no, 1=yes)
ThresholdFeatures	Enable threshold features (0=no, 1=yes)"
HingeFeatures	Enable hinge features (0=no, 1=yes)
ProductFeatures	Enable product features (0=no, 1=yes)
QuadraticFeatures	Enable quadratic features (0=no, 1=yes)
TerminateTolerance	Tolerance for detecting model convergence
NumberOfIterations	Number of iterations
NumberOfBackgroundPoints	Number of background points to be generated
mask
MinSamplesForQuadratic	Number of samples at which quadratic features start being used (only when auto features is enabled)
MinSamplesForHinge	Number of samples at which hinge features start being used (only when auto features is enabled)

Processors (8)

Name	Type	Description
select_algorithm	workflow
parse_input_points	workflow
select_layers	workflow
allocate_points	workflow
create_and_test_model	workflow
extract_aucs	workflow
calculate_mean	workflow
Flatten_List	localworker	Script flatten(inputs, outputs, depth) { for (i = inputs.iterator(); i.hasNext();) { element = i.next(); if (element instanceof Collection && depth > 0) { flatten(element, outputs, depth - 1); } else { outputs.add(element); } } } outputlist = new ArrayList(); flatten(inputlist, outputlist, 1);

Beanshells (6)

Name	Inputs	Outputs
parse_header	csv_content	name_idx id_idx long_idx lat_idx
get_first_taxon	csv_content name_idx	taxon_name
extract_taxon_points	csv_content name_idx taxon_name	taxon_points
calculate_mean	auc_list	mean_auc
allocate_points	csv_points id_idx long_idx lat_idx folds	training_points testing_points all_points num_points
create_algorithm_xml	algorithm_id algorithm_version NumberOfBackgroundPoints NumberOfIterations TerminateTolerance QuadraticFeatures ProductFeatures HingeFeatures ThresholdFeatures AutoFeatures MinSamplesForProductThreshold MinSamplesForQuadratic MinSamplesForHinge	createmodel_algorithm

Outputs (1)

Name	Description
auc

Datalinks (25)

Source	Sink
NumberOfBackgroundPoints	select_algorithm:NumberOfBackgroundPoints
NumberOfIterations	select_algorithm:NumberOfIterations
TerminateTolerance	select_algorithm:TerminateTolerance
QuadraticFeatures	select_algorithm:QuadraticFeatures
ProductFeatures	select_algorithm:ProductFeatures
HingeFeatures	select_algorithm:HingeFeatures
ThresholdFeatures	select_algorithm:ThresholdFeatures
AutoFeatures	select_algorithm:AutoFeatures
MinSamplesForProductThreshold	select_algorithm:MinSamplesForProductThreshold
MinSamplesForQuadratic	select_algorithm:MinSamplesForQuadratic
MinSamplesForHinge	select_algorithm:MinSamplesForHinge
input_points	parse_input_points:csv_content
parse_input_points:id_idx	allocate_points:id_idx
parse_input_points:lat_idx	allocate_points:lat_idx
parse_input_points:long_idx	allocate_points:long_idx
parse_input_points:taxon_points	allocate_points:csv_points
select_algorithm:algorithm	create_and_test_model:algorithm_xml
allocate_points:testing_points	create_and_test_model:testing_points
select_layers:selected_layers	create_and_test_model:layers_str
allocate_points:training_points	create_and_test_model:training_points
mask	create_and_test_model:mask
create_and_test_model:test_model_statistics	extract_aucs:test_statistics_xml
Flatten_List:outputlist	calculate_mean:auc_list
extract_aucs:auc	Flatten_List:inputlist
calculate_mean:mean_auc	auc

Coordinations (1)

Controller	Target
create_and_test_model	extract_aucs

Information Workflow Type

Taverna 2

Information Uploader

Sonja Holl

Information License

All versions of this Workflow are licensed under:

Information Version 1 (of 1)

Information Credits (2)

(People/Groups)

Information Attributions (0)

(Workflows/Files)

None

Information Tags (6)

Uploader tags

auc
|
biovel
|
enm
|
maxent
|
opimization
|
workflow

Log in to add Tags

Information Shared with Groups (0)

None

Information Featured In Packs (0)

None

Log in to add to one of your Packs

Information Attributed By (0)

(Workflows/Files)

None

Information Favourited By (0)

No one

Information Statistics

1705 viewings

1141 downloads

[ see breakdown ]

Citations (0)

None

Version History

In chronological order:

ENM Maxent workflow used for optimization

Created by Sonja Holl on Friday 09 August 2013 15:59:46 (UTC)

Last edited by Sonja Holl on Wednesday 04 September 2013 07:19:49 (UTC)

Reviews (0)

No reviews yet

Be the first to review!

Comments (0)

View Timeline

No comments yet

Log in to make a comment

Other workflows that use similar services (2)

Taverna 2

Uploader

Aleksandra Pawlik

BioVeL workshop reduced full workflow (1)

Download

The workflow is a reduced version of the main workflow. It can be used to call web services to support biodiversity research. It fetches data from GBIF. The occurrences are then used to create a model using OpenModeller, test the model and to project the model. The projection of the model is currently a "native projection" i.e. it uses the same layers as those used to create the model. The services within the workflow will allow non-native projections

Created: 2013-09-04

Credits: Katy Wolstencroft Alan Williams

Attributions:

Taverna 2

Uploader

Sonja Holl

ENM SVM workflow used for optimization (1)

Download

This workflow was used for the optimization of the SVM algorithm from the openModeller toolbox (http://openmodeller.sourceforge.net). The workflow uses 10-fold cross-validation and then calculates the average AUC, which can be used as fitness value during parameter optimization.

Created: 2013-08-09 | Last updated: 2013-09-04

Credits: Sonja Holl Renato De Giovanni

ENM Maxent workflow used for optimization

Preview

Run

Run this Workflow in the Taverna Workbench...

Workflow Components

Script

Reviews (0)

Comments (0)

Other workflows that use similar services (2)