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An ensemble classifier that consists of many decision trees and outputs the class that is the mode of the classes output by individual trees
154 questions
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How to perform Random Forest land cover classification?
This is a follow-up to a previous post: Machine Learning Algorithms for Land Cover Classification.
It seems that the Random Forest (RF) classification method is gaining much momentum in the remote ...
11
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1
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Multispectral image segmentation for natural-resources applications using R
R has the capacity for image segmentation, although all of the examples I have come across utilize a single band for the segmentation (example). I am interested in combining R's capacity for random ...
8
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Results of Variable Importance of RF Classifier in GEE
I create a RF module in GEE like this:
//Random Forest Result Function Module
exports.getRfResults = function(image, title, bands, trainPoint, testPoint, area, label) {
//Create Sample Points ...
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3
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How to generalize training data for a random forest classifier?
I am working with a random forest classifier in eCognition (new with eCognition 9.0). The image shows 8 NAIP tiles I am attempting to classify using approximately 100 training points. The training ...
6
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3
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Pixel-based and object-based classification!
I would like to understand if pixel-based classification algorithm (e.g. Maximum Likelihood classification ) can be used for object-based classification (i.e. after a segmentation procedure).
On the ...
6
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1
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Random Forest land cover classification in ArcMap?
I am an undergraduate student working with a very large data set (to me), and who has NO experience with R, but is fairly comfortable with ArcMap.
I have about 60GB of 8band 1m satellite imagery of ...
5
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2
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Random Forest to estimate land use in past with Landsat
I am new in Machine Learning and in R. I am working in my Master thesis. I am trying to estimate the LULC of the years 1984, 1990, 2000, 2011, 2014 for characterizing the forest dynamics. I have for ...
5
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2
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"User memory limit exceeded" using Random Forest classification
I am trying to classify using randomForest classification in GEE . However, I always get the error User memory limit exceeded, so I assume the number of the feature are too large.
Nevertheless, I saw ...
5
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2
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Pickling a Classifier in Google Earth Engine
I'm busy trying to create a widely applicable reedbed vegetation classifier that could potentially classify any given area within Europe. I already have training data for an area around the Balaton ...
4
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1
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Image classification random forest [duplicate]
I am a newbie in R. I want to classify images using random forest in R. I am trying to learn the codes. But in the mean time, is there a push button (like a gui) in R that can be used for ...
4
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1
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SMILE classifiers/regressors in Earth Engine
I am working on a project intended for publication that leans heavily on Earth Engine for much of the workflow: assembling, compositing, and mosaicking lots of images from multiple data sources, ...
4
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1
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Splitting up a region into training data and validation data for Landsat7 classification
I am building a classifier for Landsat7 by using MODIS land cover classification.
My goal is to split up my region of interest into 80% being training data and 20% being validation data (with a ...
4
votes
1
answer
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Calculate variable importance for classifications in Google Earth Engine
I am doing a simple Random Forest classification in Google Earth Engine. I try to classify upland, water and wetlands, using 25 variables derived from one year of Sentinel-1 images. The classifier ...
4
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1
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Performing Random-Forest Classification of 10cm Imagery for species-distribution in R (no point-shapes)? [closed]
I'm trying to classify 10cm-resolution images with the RF-package.
I do this to separate some species in the forest, seen on my images.
While I was searching for an answer, I found the following ...
4
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1
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Looking for example of a Random Forest tutorial to estimate spatial distribution
Could anyone point me to a Random Forest tutorial for predicting a spatial random variable? Or an easy dataset to try to work through.
For Decision Trees and Random Forests, I found some very good ...