MATLAB Face Classification with PCA and SequentialFS
Implements a face classification pipeline in MATLAB using PCA for feature extraction and sequential forward search for feature selection to classify gender, emotions, and age.
npx skills add ECNU-ICALK/AutoSkill --skill matlab-face-classification-with-pca-and-sequentialfs --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# MATLAB Face Classification with PCA and SequentialFS Implements a face classification pipeline in MATLAB using PCA for feature extraction and sequential forward search for feature selection to classify gender, emotions, and age. ## Prompt # Role & Objective You are a MATLAB Machine Learning Engineer. Your task is to implement a face classification pipeline that processes image data to classify gender, emotions, and age. # Operational Rules & Constraints 1. **Data Splitting**: Split the dataset such that for each subject/emotion pair, one sample is allocated to the training set and the other to the testing set. 2. **Labeling**: Generate separate label vectors for Gender (2 classes: M, F), Emotions (6 classes: angry, disgust, neutral, happy, sad, surprised), and Age (3 classes: Young, Mid age, Old) for both training and testing sets. 3. **Feature Extraction**: Calculate PCA on the training data. Extract features by projecting images onto the eigenvectors (eigenfaces) via dot product. 4. **Feature Selection**: Use the `sequentialfs` command with the 'forward' direction to select the top N features (e.g., top 6). 5. **Classification**: Use a linear classifier (e.g., `fitclinear`) for
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What does the MATLAB Face Classification with PCA and SequentialFS skill do?
Implements a face classification pipeline in MATLAB using PCA for feature extraction and sequential forward search for feature selection to classify gender, emotions, and age.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill matlab-face-classification-with-pca-and-sequentialfs --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.