: The Diagnostic Feature Designer (available via the Predictive Maintenance Toolbox ) allows you to interactively extract features and then generate MATLAB code to automate the process for future data. 3. Writing Features to Files
: Start with the function keyword, define outputs, and ensure the filename matches the function name. Example :
: After writing several feature functions, you can use algorithms like Sequential Feature Selection to identify which ones are most predictive. matlab-2017
: You can use functions like gencfeatures to perform automated feature engineering if your data is in a table.
function featureValue = getMeanAmplitude(signal) % This function calculates a simple statistical feature featureValue = mean(abs(signal)); end Use code with caution. Copied to clipboard 2. Feature Engineering Workflow : The Diagnostic Feature Designer (available via the
MATLAB R2017 introduced several tools to streamline feature creation, especially for predictive maintenance and signal processing.
In MATLAB, features are usually calculated within functions that take raw data as input and return a single value or vector. Example : : After writing several feature functions,
Introduction to Feature Selection - MATLAB & Simulink - MathWorks