search

SimonDedman / gbm.auto

Machine-learning Boosted Regression Tree software suite for species distribution modelling in R
https://doi.org/10.1371/journal.pone.0188955
Other
18 stars 6 forks source link

Auto: 3D plot #24

Open SimonDedman opened 6 years ago

SimonDedman commented 6 years ago

Maybe run this only for variable combinations with significant interactions to see if there's a shape?

SimonDedman commented 1 year ago

NFF plotly code, see https://plotly.com/r/3d-scatter-plots/

nffarabaugh commented 1 year ago

Example of a 3d scatter plot with plotly:

library(plotly)

" d3_chi_plot3 <- (plot_ly( data = reef.df3, x = ~maxn_shark, y = ~teleost_maxn, z = ~chi_benthos_percent, type = "scatter3d", mode = "markers", color = ~geo)) %>% layout( scene = list( xaxis = list( title = "Shark MaxN"), yaxis = list(title = "Pred. Teleost MaxN"), zaxis = list(title ="CCA + Hard Coral Percent Cover") ) )

d3_chi_plot3 " example_plot

SimonDedman commented 1 year ago

option to auto-export biggest interactions datasets to be plotted later if people want?

Are the biggest interactions a function of the values of the variables? If you centre and scale everything to 1, do the biggest interactions change?

@CourtneyKnaur