Added the Logistics regression data simulation in the vignette .Rmd f…

…ile.

vignettes/BackPropNN.Rmd

@@ -18,6 +18,47 @@ knitr::opts_chunk$set(
 library(BackPropNN)
 ```
 
+# Simulated data - Logistics data.
+
+```{r}
+num_obs <- 10000 # Number of observations
+
+# Setting coefficients values for the logit function.
+beta0 <- -2.5
+beta1 <- 0.02
+beta2 <- 0.01
+
+# Simulating the independent variables.
+X1 <- runif(n=num_obs, min=18, max=60)
+X2 <- runif(n=num_obs, min=100, max=250)
+prob <- exp(beta0 + beta1*X1 + beta2*X2) / (1 + exp(beta0 + beta1*X1 + beta2*X2))
+
+# Generating binary outcome variable.
+Y <- rbinom(n=num_obs, size=1, prob=prob)
+
+data <- data.frame(X1, X2, Y)
+```
+
+# Running the functions of BackPropNN package.
+
+```{r}
+set.seed(100)
+i <- 2 # number of input nodes
+h <- 4 # number of hidden nodes
+o <- 1 # number of output nodes
+learning_rate <- 0.1 # The learning rate of the algorithm
+activation_func <- "sigmoid" # the activation function
+nn_model <- back_propagation_training(i, h, o, learning_rate, activation_func, data)
+```
+
+# Summarizing the results of nn_model.
+
+```{r}
+plot(nn_model)
+summary(nn_model)
+print(nn_model)
+```
+
 # Simulated data - AND data.
 
 ```{r}