OOP for ML programming

Code pattern

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Definition

ML models are written as classes: attributes hold data and weights, methods train, predict and evaluate.

Example

model = LinearRegression(); model.fit(x, y); model.predict([[5]])

Found in: syllabus, school notes, past SDD papers.

Where you'll use it in the test

Syllabus area: Y12 Software Automation.

Question types it can appear in

Python: Write or complete it in the online Python tool.
Code reading: Code or algorithm reading: interpret a fragment and state its output or purpose.
Short answer: Define, outline or explain it and tie it to the scenario.

How to use it

A model sentence

General advice, built from the definition and example above

Code pattern: “ML models are written as classes: attributes hold data and weights, methods train, predict and evaluate.” Then apply it: model = LinearRegression(); model.fit(x, y); model.predict([[5]])

In a short answer, give the definition in your own words first, then tie it to the situation in the question. Do not copy the example above unless it fits the scenario.

Command words used with it

General advice

No linked question shows the command word for this term. Across the past python and short answer questions in this bank the words used most are: Explain, Outline, Describe, Compare, Classify, Analyse. Check the actual word in your question.

Go deeper

Flashcard: OOP for ML programming in Software Automation (Year 12) · study that set
Memorise: Decision trees
Full term page: every question, note and marking comment for OOP for ML programming

Check yourself

Write or say the “OOP for ML programming” pattern from memory: the syntax and what it does.

Reveal the answer

ML models are written as classes: attributes hold data and weights, methods train, predict and evaluate.

Example: model = LinearRegression(); model.fit(x, y); model.predict([[5]])

Could be tested as: Python, Code reading, Short answer.