Explore the pivotal stages following data transformation in model training, understanding the crucial steps beyond transformation for effective AI model development.
Table of Contents
Question
What steps are NOT part of the model training stage after data transformation?
Select all that apply.
A. Feature selection
B. Algorithm selection
C. Normalize numeric features
D. Provide a labeled dataset
E. Split data
F. Model Training
G. Scoring results
Answer
A. Feature selection
C. Normalize numeric features
Explanation
Options A and C are correct because Feature Selection and Normalize numeric features are steps from the data transformation stage and are NOT part of the model training stage.
Here is a generic workflow for model training after data pre-processing or transformation stage:
After we prepared and labeled data for the model training, we are ready to use this data set for the training.
We need to Split data before feeding it to a model training module.
We also need to select our ML algorithm to reflect our goals and be compatible with the provided data.
After that, we run the model training and produce a scoring result.
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