Home / Python / Predictive Modeling & Machine Learning / 204.5.7 The Neural Network Algorithm

204.5.7 The Neural Network Algorithm

In all previous posts we progressed to this part. We will breakdown the steps how a neural network starts and ends.

The Neural Network Algorithm

  • Step 1: Initialization of weights: Randomly select some weights
  • Step 2 : Training & Activation: Input the training values and perform the calculations forward.
  • Step 3 : Error Calculation: Calculate the error at the outputs. Use the output error to calculate error fractions at each hidden layer
  • Step 4: Weight training: Update the weights to reduce the error, recalculate and repeat the process of training & updating the weights for all the examples.
  • Step 5: Stopping criteria: Stop the training and weights updating process when the minimum error criteria is met

Randomly Initialize Weights

Training & Activation

Error Calculation at Output

Error Calculation at hidden layers

Calculate weight corrections

Update Weights

Stopping Criteria

Once Again ..Neural network Algorithm

  • Step 1: Initialization of weights: Randomly select some weights
  • Step 2 : Training & Activation: Input the training values and perform the calculations forward.
  • Step 3 : Error Calculation: Calculate the error at the outputs. Use the output error to calculate error fractions at each hidden layer
  • Step 4: Weight training : Update the weights to reduce the error, recalculate and repeat the process of training & updating the weights for all the examples.
  • Step 5: Stopping criteria: Stop the training and weights updating process when the minimum error criteria is met.

About admin

Check Also

204.7.6 Practice : Random Forest

Let’s implement the concept of Random Forest into practice using Python. Practice : Random Forest …

Leave a Reply

Your email address will not be published. Required fields are marked *