Neural network code (predict)

Code pattern Y12 Software Automation

Definition

Create the model object, train (fit) on training data, then call predict on new data to make predictions.

Example

net.fit(X, y); net.predict(new)

Found in: syllabus, course specifications, 2025 HSC marking guidelines, school notes.

Where it is used 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.

No past question in this bank is linked to this term yet. It can still be tested through the question types above.

Study links

Flashcard: Neural network code (predict) in Software Automation (Year 12) · study that set
Memorise: Decision trees

How to use it in an answer

A model sentence

General advice, built from the definition and example above

Code pattern: “Create the model object, train (fit) on training data, then call predict on new data to make predictions.” Then apply it: net.fit(X, y); net.predict(new)

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.

Technique for the question types

Python: Write code that runs: indentation, quotes, define functions before calling them, print the required output, meet every listed requirement.

Common mistakes

Marker feedback on other questions of the same type (code and diagram feedback often applies across questions)

Python questions (2025 HSC exam Q19): process string inputs; use a selection structure; code must execute in the environment; use correct indentation; call functions in the main program after defining them.
Python questions (2025 HSC exam Q26): replicate the grid; use the random library; use selection and looping to access the list; include a method of checking the number of values; use meaningful variable names and constants; avoid overly complex structures such as nested IF loops.

General advice

Use the term exactly as the syllabus words it, then link it to the scenario in the question; the 2025 feedback repeatedly rewards using the stimulus.
Answer the command word: outline gives main points only, explain gives a reason or cause, discuss gives both sides.

Same group in the syllabus: Decision tree · Neural network · Linear regression · Polynomial regression · Logistic regression · K-nearest neighbour (KNN) · OOP for ML programming

← Neural networkA to ZNeural network training and execution cycle →

← Neural networkIn Y12 Software AutomationNeural network training and execution cycle →