spnn
Scale Invariant Probabilistic Neural Networks
Scale invariant version of the original PNN proposed by Specht (1990) <doi:10.1016/0893-6080(90)90049-q> with the added functionality of allowing for smoothing along multiple dimensions while accounting for covariances within the data set. It is written in the R statistical programming language. Given a data set with categorical variables, we use this algorithm to estimate the probabilities of a new observation vector belonging to a specific category. This type of neural network provides the benefits of fast training time relative to backpropagation and statistical generalization with only a small set of known observations.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.3.0 |
rolling linux/jammy R-4.5 | spnn_1.3.0.tar.gz |
68.6 KiB |
1.3.0 |
rolling linux/noble R-4.5 | spnn_1.3.0.tar.gz |
72.5 KiB |
1.3.0 |
rolling source/ R- | spnn_1.3.0.tar.gz |
11.6 KiB |
1.3.0 |
latest linux/jammy R-4.5 | spnn_1.3.0.tar.gz |
68.6 KiB |
1.3.0 |
latest linux/noble R-4.5 | spnn_1.3.0.tar.gz |
72.5 KiB |
1.3.0 |
latest source/ R- | spnn_1.3.0.tar.gz |
11.6 KiB |
1.3.0 |
2026-04-26 source/ R- | spnn_1.3.0.tar.gz |
11.6 KiB |
1.3.0 |
2026-04-23 source/ R- | spnn_1.3.0.tar.gz |
11.6 KiB |
1.3.0 |
2026-04-09 windows/windows R-4.5 | spnn_1.3.0.zip |
477.8 KiB |
1.2.1 |
2025-04-20 source/ R- | spnn_1.2.1.tar.gz |
11.5 KiB |