Geoinformatics
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From GIS to Remote Sensing: Monitoring Changes in the Amazon Rainforest: a Tutorial Using the Semi-Automatic Classification Plugin

From GIS to Remote Sensing: Monitoring Changes in the Amazon Rainforest: a Tutorial Using the Semi-Automatic Classification Plugin | Geoinformatics | Scoop.it
RT @InfoAmazonia: From GIS to Remote Sensing: Monitoring Changes in the Amazon Rainforest: a Tutorial http://t.co/U53Wv7pbaG
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Cheat sheet for prediction and classification models in R

Cheat sheet for prediction and classification models in R | Geoinformatics | Scoop.it
Ricky Ho has created a reference a 6-page PDF reference card on Big Data Machine Learning, with examples implemented in the R language.

Via M. Edward (Ed) Borasky, Dahl Winters
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Feature Selection with Scikit-Learn

Feature Selection with Scikit-Learn | Geoinformatics | Scoop.it

In the code below, I compute the accuracies with various feature sizes for 9 different classifiers, using both the Chi-squared measure and the ANOVA F measures.


Via Dahl Winters, Ramnandan Krishnamurthy
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Scikit-learn: Feature Extraction From Text

Scikit-learn: Feature Extraction From Text | Geoinformatics | Scoop.it
I've been playing with scikit-learn recently, a machine learning package for Python. While there's great documentation on many topics, feature extraction isn't one of them. My use case was to turn ...

Via Arthur
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Intro to scikit-learn (II), SciPy2013 Tutorial, Part 1 of 2

Presenters: Gaël Varoquaux, Jake Vanderplas, Olivier Grisel Description Machine Learning is the branch of computer science concerned with the development of ...
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Machine Learning For Remote Sensing : Orfeo ToolBox Meets OpenCV

Orfeo ToolBox is an open-source library developed by CNES in the frame of the Orfeo program since 2006, which aimed at preparing institutional and scientific users to the use of the Very High Resolution optical imagery delivered by the Pleiades satellites. It is written in C++ on top of ITK, a medical imagery toolkit, and relies on many other open-source libraries such as GDAL or OSSIM. The OTB aims at providing generic means of pre-processing and information extraction from optical satellites imagery. In this talk, we will focus on recent advances in the machine learning functionality allowing to use the full extent of OpenCV algorithms.


Via Dahl Winters
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Random Forests Algorithm: Background and Uses

Random Forests Algorithm: Background and Uses | Geoinformatics | Scoop.it
One of the most popular methods or frameworks used by data scientists at the Rose Data Science Professional Practice Group is Random Forests. The Random For…

Via Dahl Winters
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scikit-learn: machine learning in Python

scikit-learn: machine learning in Python | Geoinformatics | Scoop.it

scikit-learn. Machine Learning in Python. Simple and efficient tools for data mining and data analysis; Accessible to everybody, and reusable in various contexts; Built on NumPy, SciPy, and matplotlib


Via Danen Raas
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Random Forest Regression and Classification in R and Python

Random Forest Regression and Classification in R and Python | Geoinformatics | Scoop.it
When I build the regression models for both Python and R I got totally different results. The scikit-learn version produced an R2 value ~0.72 where as the R version was ~0.63. In addition the MSE for R was 0.64 and 0.42 for Python.

Via Danen Raas
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