Overview#

Machine Learning model is the model of an Artificial Neural network

Machine Learning models (and Statistics Models) the Bias error–Variance error tradeoff (or dilemma) is the problem of simultaneously minimizing two sources of error that prevent Supervised Learning Mapping function from generalizing beyond their Training dataset:

• underfitting
• overfitting

Recommended #

Solve high Bias error (Underfitting) first then high Variance error (overfitting).

More Information#

There might be more information for this subject on one of the following:

• Analytics
• Behavioral analytics
• Bias error
• Classification Trees
• Dropout Regularization
• Hyperparameters
• Machine Learning Algorithms
• Metadata
• Supervised Learning
• Surveillance
• Training dataset
• Underfitting