Implementation of backpropagation artificial neural networks in Julia.
Pkg.clone("git@github.com:EricChiang/ANN.jl.git")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.
fit!andpredictcurrently require Float64 matrices and vectors.