Performance Assessment of Certain Machine Learning Models for Predicting the Major Depressive Disorder among IT Professionals during Pandemic times

Algorithm 2

	Input. The selected features from the correlation-based feature selection
	Initialize the values of weights, biases, and the learning rate (α)
	Do
	For every input do Feedforward:
	Process the inputs one by one: , where ‘n’ stands for the total number of samples
	Output:
	output calculation with the activation function:
	Adjust weight and bias:
	if ‘b’ not equals to target ‘t’ then update the weights
	Stopping condition
	Gradient descent calculation with respect to each error due to the selected weights
	Where are the initial target value and the obtained output
	Repeat the similar calculation and updation of new weights continues at the hidden layer
	Output. Classification results and error rate.