Implementation of backpropagation artificial neural networks in Julia.
Install (from within Julia interpreter):
using ANN n_hidden_units = 20 ann = ArtificialNeuralNetwork(n_hidden_units) n_obs = 150 n_feats = 80 X = rand(Float64, n_obs, n_feats) y = rand(Int64, n_obs) fit!(ann, X, y) n_new_obs = 60 X_new = rand(Float64, n_new_obs, n_feats) y_pred = predict(ann, X_new)
- Allow users to build multilayer networks
- Accept DataFrames as inputs.
predictcurrently require Float64 matrices and vectors.