Phase where the appropriate algorithm is chosen for the task?

Phase where the appropriate algorithm is chosen for the task?

• A. Model selection
• B. Data collection and preprocessing
• C. Definition of problem or task
• D. Model training

Answer: (A)

Choosing the modeling approach is the phase where the appropriate algorithm is chosen. After defining the task and preparing the data, you evaluate which algorithms could address the problem given the data characteristics, performance needs, and constraints, and you select the one that best fits. This sets up what will be trained next. Data collection and preprocessing focus on preparing clean, usable data, not on selecting the method. Defining the problem clarifies what you’re trying to achieve but doesn’t decide which algorithm to apply. Model training is the step that actually learns from the data using the chosen algorithm.

Choosing the modeling approach is the phase where the appropriate algorithm is chosen. After defining the task and preparing the data, you evaluate which algorithms could address the problem given the data characteristics, performance needs, and constraints, and you select the one that best fits. This sets up what will be trained next. Data collection and preprocessing focus on preparing clean, usable data, not on selecting the method. Defining the problem clarifies what you’re trying to achieve but doesn’t decide which algorithm to apply. Model training is the step that actually learns from the data using the chosen algorithm.