Finds nearest neighours and the minimum spanning tree for
large data sets, does clustering using the minimum spanning
tree.

'NEON' 'API' (<http://data.neonscience.org/data-api>) client.
Includes methods for interacting with all 'API' routes.
c(
person("Scott", "Chamberlain", role = c("aut", "cre"),
email = "myrmecocystus+r@gmail.com"),
person("Josh", "Roberti", role = "ctb")
)
crul (>= 0.1.0), jsonlite (>= 1.1), tibble (>= 1.2),
data.table, fauxpas
Scott Chamberlain [aut, cre],
Josh Roberti [ctb]

Software for feed-forward neural networks with a single
hidden layer, and for multinomial log-linear models.
Feed-forward Neural Networks and Multinomial Log-Linear Models

Feed-Forward Neural Networks and Multinomial Log-Linear Models

Prediction Intervals of Multi-Layer Neural Networks
Computing prediction intervals of neural network models (e.g.backpropagation) at certain confidence level. It can take the output from models trained by other packages like 'nnet', 'neuralnet', 'RSNNS', etc.

Time Series Forecasting with Neural Networks
person("Nikolaos", "Kourentzes", email = "nikolaos@kourentzes.com",
role = c("aut", "cre"))
Contains functions to facilitate automatic time series modelling with neural networks.
Allows fully automatic, semi-manual or fully manual specification of networks. For details of the
specification methodology see: (i) Crone and Kourentzes (2010) <doi:10.1016/j.neucom.2010.01.017>;
and (ii) Kourentzes et al. (2014) <doi:10.1016/j.eswa.2013.12.011>.

Automatic time series modelling with neural networks.
Allows fully automatic, semi-manual or fully manual specification of networks. For details of the
specification methodology see: (i) Crone and Kourentzes (2010) <doi:10.1016/j.neucom.2010.01.017>;
and (ii) Kourentzes et al. (2014) <doi:10.1016/j.eswa.2013.12.011>.
glmnet, neuralnet, plotrix, MASS, tsutils, uroot

forecast, glmnet, neuralnet, plotrix, MASS, tsutils, uroot,
methods

k-Nearest Neighbor Join for Spatial Data
K-nearest neighbor search for projected and non-projected 'sf' spatial layers. Nearest neighbor search uses (1) function nn2() from package 'RANN' for projected point data, or (2) function st_distance() from package 'sf' for other types of spatial data.