Increasingly becoming a necessity in Ecology and Earth Science research, handling complex data can be a tough nut when traditional statistical methods are applied. As its first publication, the new technologically-advanced Open Access journal One Ecosystem features a review paper describing the benefits of using machine learning technologies when working with highly-dimensional and non-linear data. Natural sciences, such as Ecology and Earth science, focus on the complex interactions between biotic and abiotic systems in order to infer understand these systems and make predictions. Traditional statistical methods can impose unrealistic assumptions that result in unsound conclusions as the era of'big data' meets ecology and earth science. Machine-learning-based methods, capable of inferring missing data and handling complex interactions, are more apt for handling complex scientific data.

Increasingly becoming a necessity in Ecology and Earth Science research, handling complex data can be a tough nut when traditional statistical methods are applied. As its first publication, the new technologically-advanced Open Access journal One Ecosystem features a review paper describing the benefits of using machine learning technologies when working with highly-dimensional and non-linear data. Natural sciences, such as Ecology and Earth science, focus on the complex interactions between biotic and abiotic systems in order to infer understand these systems and make predictions. Traditional statistical methods can impose unrealistic assumptions that result in unsound conclusions as the era of'big data' meets ecology and earth science. Machine-learning-based methods, capable of inferring missing data and handling complex interactions, are more apt for handling complex scientific data.

IMAGE: This plot shows the proportion of articles about machine learning in four natural science disciplines from 1994 to 2015, illustrating the slow penetration of the method in three of four... view more Increasingly becoming a necessity in Ecology and Earth Science research, handling complex data can be a tough nut when traditional statistical methods are applied. As one of its first publications, the new technologically-advanced Open Access journal One Ecosystem features a review paper describing the benefits of using machine learning technologies when working with highly-dimensional and non-linear data. Natural sciences, such as Ecology and Earth science, focus on the complex interactions between biotic and abiotic systems in order to infer understand these systems and make predictions. Traditional statistical methods can impose unrealistic assumptions that result in unsound conclusions as the era of'big data' meets ecology and earth science. Machine-learning-based methods, capable of inferring missing data and handling complex interactions, are more apt for handling complex scientific data.

Increasingly becoming a necessity in Ecology and Earth Science research, handling complex data can be a tough nut when traditional statistical methods are applied. As its first publication, the new technologically-advanced Open Access journal One Ecosystem features a review paper describing the benefits of using machine learning technologies when working with highly-dimensional and non-linear data. Natural sciences, such as Ecology and Earth science, focus on the complex interactions between biotic and abiotic systems in order to infer understand these systems and make predictions. Traditional statistical methods can impose unrealistic assumptions that result in unsound conclusions as the era of'big data' meets ecology and earth science. Machine-learning-based methods, capable of inferring missing data and handling complex interactions, are more apt for handling complex scientific data.