Huettmann F, Craig EH, Herrick KA, Baltensperger AP, Humphries GRW, Lieske DJ, Miller K, Mullet TC, Oppel S, Resendiz C, Rutzen I, Schmid MS, Suwal MK, Young BD (2018) Use of Machine Learning (ML) for Predicting and Analyzing Ecological and “Presence Only” Data: An Overview of Applications and a Good Outlook. In: Machine Learning for Ecology and Sustainable Natural Resource Management, 2nd edn. Springer International Publishing, Cham, p 27–61
Publication year: 2018

2.1 Introduction

Over a decade ago, Leo Breiman (2001a) wrote: “There are two cultures in the use

of statistical modeling to reach conclusions from data. One assumes that the data

are generated by a given stochastic data model. The other uses algorithmic models

and treats the data mechanism as unknown. The statistical community has been

committed to the almost exclusive use of data models. This commitment has led to

irrelevant theory, questionable conclusions, and has kept statisticians from working

on a large range of interesting current problems. Algorithmic modeling, both in

theory and practice, has developed rapidly in fields outside statistics.”

 

More at: https://www.researchgate.net/publication/328756751_Use_of_Machine_Learning_ML_for_Predicting_and_Analyzing_Ecological_and_’Presence_Only’_Data_An_Overview_of_Applications_and_a_Good_Outlook

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