Predictive Modeler
A Predictive Modeler is a modeler who can perform a predictive modeling task (able to produce a predictive model).
- Example(s)
- Counter-Example(s):
- See: Predictive Model.
References
2013
- (de Fortuny Enric et al., 2013) ⇒ Junqué de Fortuny Enric, Martens David, and Provost Foster. (2013). “Predictive Modeling With Big Data: Is Bigger Really Better?.” In: Big Data, 1(4): 215-226. doi:10.1089/big.2013.0037.
- QUOTE: … We introduce a version of Naïve Bayes with a multivariate event model that can scale up efficiently to massive, sparse datasets. Specifically, this version of the commonly used multivariate Bernoulli Naïve Bayes only needs to consider the “active” elements of the dataset — those that are present or non-zero — which can be a tiny fraction of the elements in the matrix for massive, sparse data. This means that predictive modelers wanting to work with the very convenient Naïve Bayes algorithm are not forced to use the multinomial event model simply because it is more scalable. This article thereby makes a small but important addition to the cumulative answer to a current open research question17: How can we learn predictive models from lots of data?