Secom-Dataset

Dataset Overview

Dataset Name

Predictive‑Models‑for‑Equipment‑Fault‑Detection---Secom‑Dataset

Composition

• secom.data: Contains 1,567 observations with 590 variables (features).
• secom_labels.data: Contains classification labels (pass/fail) and timestamps.

Description

• secom.data: Each record represents a production entity with a set of measured features.
• secom_labels.data: Simple pass/fail labeling where –1 indicates pass, 1 indicates fail; timestamps correspond to specific test points.

Applications

• Apply various machine‑learning models for fitting, evaluate model performance, and select the best model to predict yield in semiconductor manufacturing.

Special Note

• The data involve a rare‑event statistical scenario; the occurrence frequency of the failure class is extremely low, so sampling techniques are applied during preprocessing.