This week's #KeyAlgorithms article discusses #RandomForests
https://playfultechnology.co.uk/random-forests.html
#DataScience #MachineLearning
@data_science
This week's #KeyAlgorithms article discusses #RandomForests
https://playfultechnology.co.uk/random-forests.html
#DataScience #MachineLearning
@data_science
Here is an example of using #RandomForests ๐ณ๐ณ for #PixelClassification ๐ผ๏ธ in #Python ๐, using @napari for labeling โ๏ธ
๐ https://www.fabriziomusacchio.com/blog/2023-06-23-_random_forests_pixel_classifier/
#RandomForest #Napari #MachineLearning #ImageProcessing #Bioimage #BioimageAnalysis
Ever wondered how #DecisionTrees and #RandomForests ๐ณ๐ณ are related? Here is a quick #tutorial that compares both methods in terms of #classification and #regression โ๏ธ
๐ https://www.fabriziomusacchio.com/blog/2023-06-22-_decision_trees_vs_random_forests/
A novel method for #posthoctesting: โA short note on post-hoc testing using #randomforests algorithm: Principles, asymptotic Time complexity analysis, and beyondโ by L. ล tฤpรกnek, F. Habarta, I. Mala, L. Marek.
@FedCSIS
2022, ACSIS Vol. 30 p. 489โ497; http://tinyurl.com/yytek6up
In my opinion, #R is very suitable for #MachineLearning. With R, machine learning can be easily integrated into usual #rstats data analysis workflows. #RPackages provide access to virtually all relevant machine learning algorithms like #NeuralNetworks, Support Vector machines (#SVM), #RandomForests, Extreme Gradient Boosting (#XGBoost), #WEKA algorithms, etc.
Does anyone of the @rstats group have further recommendations?
See reply for sources: 4 books on machine learning.
trying to capture #RandomForests questions in metaphor:
- will the Amazon algorithm (corporation) learn to appreciate the Amazon river?
- and what if this actually determines the fate of the Amazon basin?
- will Amazon just sew the river if we give it rights as a legal person?