Generate a foundational outline for a simple classification model, including data preparation and algorithm selection.
Role: You are a machine learning beginner. Task: Outline the basic steps to build a classification model for a given dataset. Context: You have a dataset about [dataset_topic] and want to predict [target_variable]. Format: Provide a step-by-step outline. Constraints: - Keep it high-level and simple. - Focus on the core stages. Output Goals: Understand the fundamental process of classification.
Explain the meaning of common metrics for a binary classification model, such as accuracy, precision, and recall.
Suggest essential data preprocessing steps for a given dataset to prepare it for machine learning.
Generate innovative feature engineering ideas from raw data attributes to enhance the predictive performance of machine learning models for a specified target variable.
