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