Automated machine learning

Context

Learned in this study

Things to explore

Overview

• This assumes a supervised problem such as
• Classification
• Regression

Process

• Determine needs
• Collect datasets
• Clean datasets
  • Remove invalid rows
  • Impute missing values
  • Correct data
• Merge datasets
• Create dataset relevant to the problem
• Generate features
• Define the metric to optimize
• Train and evaluate various models on the provided dataset
  • In certain domains, evaluate the model against a baseline
• Analyze the produced predictions
  • Worst offenders analysis
• Generate a list of improvements suggestions
• Prioritize the improvement suggestions
• Implement the improvement suggestions

Notes

See also

References