# Simple Vibe Prompt — Module 4: Secondary Structure Prediction

Load `data/converted_data.csv`. Use 1% of rows. Keep only proteins whose sequence uses standard amino acids (ACDEFGHIKLMNPQRSTVWY) and whose sequence and structure columns are the same length.

For each residue, encode a sliding window of 17 amino acids as a one-hot vector (17×20=340 features). The label is the secondary structure character (H/E/C) at the centre position.

Use sklearn's MLPClassifier (one hidden layer of 20 neurons) on a 70/30 split. Report Q3 accuracy (overall % correct) and a confusion matrix. Save to `outputs/module4_confusion_test_simple.csv` and `outputs/module4_metrics_simple.json`.
