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The Secom dataset contains a unique rare‑event scenario with highly imbalanced output classes. It consists of 1,567 observations and 590 variables; each record represents a single production entity with associated measurement features. The `secom_labels.data` file provides pass/fail labels (‑1 = pass, 1 = fail) and timestamps for each test point.

The dataset comprises a series of wireless sensor network measurement records with injected faults of various types. It contains 281,280 observations (vectors), each with 12 attributes. The original data stem from a 2010 study by researchers at the University of North Carolina at Greensboro, collected using TelosB nodes from single‑hop and multi‑hop wireless sensor networks measuring humidity and temperature. The prepared dataset focuses on outdoor multi‑hop WSN data, containing 4,688 observations, each comprising three consecutive time points of two temperature and two humidity measurements, with random injection of different fault types and proportions.