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The Forest for the Trees: Making Predictions using Forest-Based Classification and Regression 

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This workshop will cover the basics of how the widely-used machine learning approach, random forest, can be used to solve complex spatial problems and make effective predictions. Learn how the Forest-based Classification and Regression tool enables you to bring together both vector and raster data in powerful ways to solve problems in the areas of both classification (predicting a categorical variable) and regression (predicting a continuous variable). Explore how to evaluate your model using a number of validation techniques and diagnostics.
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30 июл 2019

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Комментарии : 7   
@farahnusrat5639
@farahnusrat5639 2 года назад
Excellent tutorial with a great explanation. Really helpful. If you can provide the input and output data, that will be really helpful to understand more clearly.
@chatoba3298
@chatoba3298 Год назад
Thank you for sharing this video. It was very well explained, easy to follow for beginners.
@sy.raihana
@sy.raihana Год назад
Hi, how can I set different variable to predict?
@abdukhatir7187
@abdukhatir7187 Год назад
how to create/obtain lower slope, upper slope (cool), upper slope (neutral) and upper slope (warm)????
@vidushipatel9226
@vidushipatel9226 3 года назад
Hi I am trying to use this tool but can't get an option of adding raster as explanatory variable. Any help is greatly appreciated.
@geospatialdatascientist
@geospatialdatascientist 3 года назад
I am also having the same problem. I wonder whether you solve it?
@jaileencmercedhoyos1576
@jaileencmercedhoyos1576 2 года назад
I found the solution, make sure to select the "Forest-based Classification and Regression" the second choice which is (Spatial Statistics Tool). Not the first option (GeoAnalytics Desktop Tool).
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