Archive For The “Machine Learning” Category

Automated Ontology Building in Ecology

Automated Ontology Building in Ecology

One of the more difficult aspects of trying to apply “big data” thinking in ecology is the massive heterogeneity of terms. I stumble over this issue every time I work on a data set for the Encyclopedia of Life. The many different ways to describe the same habitat (among other things) and the varying granularity…

Keystone Predators and Centrality: Ecosystem as Social Network Part 2

Keystone Predators and Centrality: Ecosystem as Social Network Part 2

My last post looked at a very small, but well studied rocky intertidal ecosystem and was able to identify a keystone predator (Pisaster) in a network using centrality measures. I was worried, though, that this method would not work on a larger, more complicated system. Let’s try these same calculations on a slightly larger kelp…

Keystone Predators and Centrality: Ecosystem as Social Network Part 1

Keystone Predators and Centrality: Ecosystem as Social Network Part 1

A few weeks ago I announced a project that would train an algorithm to recognize important taxa in an ecosystem using the characteristics of species interactions within that ecosystem. This post documents the first bit of work I’ve done. I’ve made a github repo with data and code. I’m using Python 2.7 with NetworkX. First I…

Ecosystem as Social Network

Ecosystem as Social Network

Lately, I’ve been thinking about how interactions between organisms in an ecosystem can be represented as a graph, with nodes and edges, similar to a social network. The nodes represent an organism or group of organisms while the edges represent the relationship between them. For example, a graph representation of an African savanna ecosystem would…

How Fair is Big Data?

“Big Data” and machine learning are used in a wide variety of disciplines, from making credit and insurance decisions to driving medical research, but how accurate is this approach? If algorithms are ground-truthed used a biased population, the results of those algorithms will also be biased. Alex Lancaster has a great post on his blog…

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