Neural Networks Example

Neural Networks Example

Problem Statement

Use the Neural Network model to predict the values for gear based on the other variables. 

How to perform analysis

Step 1: Open Sigma Magic
  1. Click on the Sigma Magic button on the Excel toolbar.
  2. Click on the New button to create a new project.
Step 2: Add the analysis template
  1. Click on the Tool Wizard to add the analysis template.
  2. Click on Analytics and then Neural Networks.


Step 3: Specify analysis options
A new worksheet will be added to your workbook. Analysis Setup will be automatically opened, in the setup tab specify the survey results.


Click on Data to specify the data required for this analysis.




Click on the Train the software will let you pick the options for training the given model. Training is a step where we split the data into groups a train data set and a test data set. 



Click on the Tuning to identifying the best set of hyperparameters that gives the best fit for the given model. 


Click the Verify tab to ensure all the inputs are okay and shown in a green checkmark.



Step 4: Generate analysis result
Click OK and then click Compute Outputs to get the final results.



Interpretation of Results

  • The neural network model has an accuracy of 86.48%, indicating good classification performance.
  • The hyperparameter tuning graph suggests model performance improvements with specific tuning configurations.
  • The variable importance plot highlights key features impacting predictions, which helps in understanding model behavior and refining input features.
  • Training data consists of 29 rows, while predictions are based on 0 rows, meaning the evaluation might be limited in terms of unseen data testing.
  • Various fitting reports show evaluation metrics like t-values and residuals, which help assess model reliability.
  • The model is a classification model using a bagging method and random modulation tuning, implying robustness in handling different data distributions.

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