Description

Logistic regression is a generalised linear model that maps features to a class probability via the logistic / softmax link. It is the calibration-friendly linear baseline in CSI sensing — interpretable coefficients, well-defined uncertainty, fast inference — and is the default head on top of CNN/Transformer feature backbones.

When it's used

  • Linear baseline for hand-crafted CSI features
  • Final classification layer of deep models
  • Calibrated-probability estimators

Limitations

  • Cannot model non-linear feature interactions without explicit basis expansion
  • Underperforms ensembles on raw subcarrier features

Source Papers

  • hou2023_bf83 — LR baseline among few-shot CSI classifiers
  • esrafiliannajafabadi2022_1342 — LR among CSI baselines
  • chen2018_97e0 — LR occupancy classifier
  • shahbazian2023_1172 — LR-based localisation baseline

30 vault papers use this method

Titles and DOIs only — no abstracts, no analyses.

  • Device-free occupancy detection and crowd counting in smart buildings with WiFi-enabled IoT 2018 DOI ↗
  • DASECount: Domain-Agnostic Sample-Efficient Wireless Indoor Crowd Counting via Few-Shot Learning 2023 DOI ↗
  • Human Sensing by Using Radio Frequency Signals: A Survey on Occupancy and Activity Detection 2023 DOI ↗
  • A Non Intrusive Human Presence Detection Methodology Based on Channel State Information of Wi-Fi Networks 2023 DOI ↗
  • Building occupancy estimation and detection: A review 2018 DOI ↗
  • Simultaneous Crowd Estimation in Counting and Localization Using WiFi CSI 2021 DOI ↗
  • Simultaneous Crowd Estimation in Counting and Localization Using WiFi CSI 2021 DOI ↗
  • Simultaneous Crowd Estimation in Counting and Localization Using WiFi CSI 2021 DOI ↗
  • Simultaneous Crowd Estimation in Counting and Localization Using WiFi CSI 2021 DOI ↗
  • Simultaneous Crowd Estimation in Counting and Localization Using WiFi CSI 2021 DOI ↗
  • Simultaneous Crowd Estimation in Counting and Localization Using WiFi CSI 2021 DOI ↗
  • Simultaneous Crowd Estimation in Counting and Localization Using WiFi CSI 2021 DOI ↗
  • Simultaneous Crowd Estimation in Counting and Localization Using WiFi CSI 2021 DOI ↗
  • Simultaneous Crowd Estimation in Counting and Localization Using WiFi CSI 2021 DOI ↗
  • A Survey on Green Wireless Sensing: Energy-Efficient Sensing via WiFi CSI and Lightweight Learning 2026 DOI ↗
  • Data-driven queueing modelling: a simulation case study of emergency department crowding 2026 DOI ↗
  • Learning from LLM Disagreement in Retrieval Evaluation 2025 DOI ↗
  • Analysing and Predicting Success of Crowdfunding Campaigns 2024 DOI ↗
  • Identifying Science and Technology Priorities Using Domain Knowledge and Pre-trained Model 2024 DOI ↗
  • Training a Geographic Entity Recognizer on Biomedical Abstracts with the Aid of Embeddings, Metadata, and Linked Data 2024 DOI ↗
  • CSI-Based People Counting in WiFi Networks: Leveraging Occupancy Detection 2024 DOI ↗
  • AI-based Occupancy Prediction using WiFi CSI 2024 DOI ↗
  • Edge-Based Real-Time Occupancy Detection System through a Non-Intrusive Sensing System 2023 DOI ↗
  • Edge-Based Real-Time Occupancy Detection System through a Non-Intrusive Sensing System 2023 DOI ↗
  • Edge-Based Real-Time Occupancy Detection System through a Non-Intrusive Sensing System 2023 DOI ↗
  • Edge-Based Real-Time Occupancy Detection System through a Non-Intrusive Sensing System 2023 DOI ↗
  • Data Assimilation for Agent-Based Models 2023 DOI ↗
  • Edge-Based Real-Time Occupancy Detection System through a Non-Intrusive Sensing System 2023 DOI ↗
  • Edge-Based Real-Time Occupancy Detection System through a Non-Intrusive Sensing System 2023 DOI ↗
  • A Framework to Estimate Classroom Occupancy using WiFi Channel State Information 2023 DOI ↗