The cnnlstm package provides functions to carry out the methodology CNN-LSTM in R:
Split data
Generate CNN models to smooth the data obtained by sensors
Generate LSTM models to predict a variable with nonlinear behavior over time
Evaluate performance of prediction model
Installation
You can install the development version of cnnlstm from GitHub. It is recommended to follow these steps to avoid problems when using the package:
# Step 1: Install the reticulate package
install.packages("reticulate")
library(reticulate)
# Step 2: Install the tensorflow package
## Option 1:
install.packages("tensorflow")
library(tensorflow)
## Option 2:
install.packages("remotes")
remotes::install_github("rstudio/tensorflow"))
library(tensorflow)
# Step 3: Validate if python is installed on the system. If it is installed, continue to the next step. For the installation:
## Option 1: Download python www.python.org/download
## Option 2:
reticulate::install_python()
# Step 4: Use the install_tensorflow() funcion to install the TensorFlow module
install_tensorflow(envname = "r-tensorflow")
# Step 5: Install the keras package
install.packages("keras")
library(keras)
install_keras()
# Step 6: Confirm that Tensorflow installation succeeded
tf$constant("Hello Tensorflow!")
# Step 7: Install the devtools package
install.packages("devtools")
# Step 8: Install and load the cnnlstm package
devtools::install_github("cjrincon/cnnlstm")
library(cnnlstm)Examples
You can visit the package website to explore the functions, documentation and examples.
