openModeller id: CONSENSUS
Current version: 0.2 Developer(s): Renato De Giovanni
Accepts Categorical Maps: no
Requires absence points: no
Author(s): Renato De Giovanni
This is a kind of meta algorithm that receives other algorithms as parameters so that it can generate the individual models and then merge the results into an aggregated model. The maximum number of algorithms is limited to 5. Leave the algorithm parameter blank if you want to use fewer algorithms. IMPORTANT: To specify an algorithm you need to know the algorithm id and its parameters names in openModeller (you can do this by inspecting the request.txt file that comes as an exemple in the command-line interface). Before merging the models, each individual model is transformed into a binary model using the lowest presence threshold. You can assign different weights to each algorithm and also specify the minimum level of agreement between the algorithms. A minimum level of 3 when 5 algorithms are used means that, when less than 3 algorithms agree on a prediction, the result will be zero, so the final model only shows areas where the specified number of algorithms agree on the prediction.
Algorithm1
openModeller id: Alg1
First algorithm to be used in the consensus. It must be specified by its id followed by a sequence of parameter_name=parameter_value separated by comma and enclosed by a parentheses, such as: RF(NumTrees=10,VarsPerTree=0,ForceUnsupervisedLearning=0). Existing algorithm ids and parameter names can be found in the end of the om_console request file that comes with the openModeller command line interface.
Data type: string Typical value: RF(NumTrees=10,VarsPerTree=0,ForceUnsupervisedLearning=1)
Algorithm2
openModeller id: Alg2
Second algorithm to be used in the consensus. It must be specified by its id followed by a sequence of parameter_name=parameter_value separated by comma and enclosed by a parentheses, such as: RF(NumTrees=10,VarsPerTree=0,ForceUnsupervisedLearning=0). Existing algorithm ids and parameter names can be found in the end of the om_console request file that comes with the openModeller command line interface. Leave empty if you don't want to use any further algorithms
Data type: string Typical value:
Algorithm3
openModeller id: Alg3
Third algorithm to be used in the consensus. It must be specified by its id followed by a sequence of parameter_name=parameter_value separated by comma and enclosed by a parentheses, such as: RF(NumTrees=10,VarsPerTree=0,ForceUnsupervisedLearning=0). Existing algorithm ids and parameter names can be found in the end of the om_console request file that comes with the openModeller command line interface. Leave empty if you don't want to use any further algorithms
Data type: string Typical value:
Algorithm4
openModeller id: Alg4
Fourth algorithm to be used in the consensus. It must be specified by its id followed by a sequence of parameter_name=parameter_value separated by comma and enclosed by a parentheses, such as: RF(NumTrees=10,VarsPerTree=0,ForceUnsupervisedLearning=0). Existing algorithm ids and parameter names can be found in the end of the om_console request file that comes with the openModeller command line interface. Leave empty if you don't want to use any further algorithms
Data type: string Typical value:
Algorithm5
openModeller id: Alg5
Fifth algorithm to be used in the consensus. It must be specified by its id followed by a sequence of parameter_name=parameter_value separated by comma and enclosed by a parentheses, such as: RF(NumTrees=10,VarsPerTree=0,ForceUnsupervisedLearning=0). Existing algorithm ids and parameter names can be found in the end of the om_console request file that comes with the openModeller command line interface. Leave empty if you don't want to use any further algorithms
Data type: string Typical value:
Weights
openModeller id: Weights
Sequence of weights, each one related to the corresponding algorithm, separated by space. This can be used to give more importance to certain algorithms. Use dot as decimal separator.
Data type: string Typical value: 1.0 0.0 0.0 0.0 0.0
Agreement
openModeller id: Agreement
Minimum level of agreement between the algorithms. Only predictions that are agreed between the specified number of algorithms will be returned as a positive value.
Data type: integer Domain: [1.0, 5.0] Typical value: 1