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Requirements Clarification & Assessment
Objective:
Develop a clustering model to categorize basketball athletes based on their attributes, allowing for tailored practice sessions and improvement strategies.
Data Requirements:
Historical Player Data: Collect comprehensive data on players' attributes, including physical attributes (height, weight), performance metrics (shooting accuracy, defensive skills), and psychological traits (teamwork, leadership).
Data Sources: Utilize structured formats such as Excel or relational databases to store and manage data efficiently.
Attribute Selection:
Identify key features that significantly impact player performance and development, ensuring a holistic view of each athlete.
Stakeholder Engagement:
Collaborate with coaches, scouts, and team management to align on the attributes and objectives of the clustering model. Their insights will guide feature selection and validation processes.