Figure 4
The bar graph compares error rates against the number of layers in a neural network using the Tanh activation function. The x-axis represents the number of layers, with values at 0, 1, 2, 4, and 6. The y-axis represents the error rate, ranging from 0 to 60. There are five vertical bars, each representing a different number of layers. The error rates for each number of layers are as follows: 0 layers has an error rate of approximately 20, 1 layer has an error rate of approximately 2, 2 layers has an error rate of approximately 15, 4 layers has an error rate of approximately 35, and 6 layers has an error rate of approximately 52. The bars are colored blue. The graph indicates that as the number of layers increases, the error rate generally increases, with a notable spike at 6 layers. All values are approximated.Comparative analysis of error rates by number of layers using the Tanh activation function