diff --git a/dev/.documenter-siteinfo.json b/dev/.documenter-siteinfo.json index 4c9ce52..c274ee5 100644 --- a/dev/.documenter-siteinfo.json +++ b/dev/.documenter-siteinfo.json @@ -1 +1 @@ -{"documenter":{"julia_version":"1.10.2","generation_timestamp":"2024-03-22T14:45:17","documenter_version":"1.3.0"}} \ No newline at end of file +{"documenter":{"julia_version":"1.10.2","generation_timestamp":"2024-03-25T15:52:41","documenter_version":"1.3.0"}} \ No newline at end of file diff --git a/dev/index.html b/dev/index.html index 564d4d9..b15f15d 100644 --- a/dev/index.html +++ b/dev/index.html @@ -37,4 +37,4 @@ Use a maxnet model to predict on new data.
Arguments
m
: a MaxnetModel as returned by maxnet
x
: a Tables.jl
-compatible table of predictors. All columns that were used to fit m
should be present in x
Keywords
link
: the link function used. Defaults to CloglogLink(), which is the default on the Maxent Java appliation since version 4.3. Alternatively, LogitLink() was the Maxent default on earlier versions. To get exponential output, which can be interpreted as predicted abundance, use LogLink() IdentityLink() returns the exponent without any transformation.clamp
: If true
, values in x
will be clamped to the range the model was trained on. Defaults to false
.Returns
A Vector
with the resulting predictions.
Example
using Maxnet
p_a, env = Maxnet.bradypus();
bradypus_model = maxnet(p_a, env; features = "lq")
-prediction = Maxnet.predict(bradypus_model, env)
sourceSettings
This document was generated with Documenter.jl version 1.3.0 on Friday 22 March 2024. Using Julia version 1.10.2.