Essays about: "Receiver Operating Curve"

Showing result 11 - 15 of 40 essays containing the words Receiver Operating Curve.

  1. 11. Encoding Temporal Healthcare Data for Machine Learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Tamás Laczik; [2021]
    Keywords : Machine Learning; Temporal Data; Disease Prediction; Feature Engineering; Random Forest; Logistic Regression; Maskininlärning; tidsdata; förutsägelse av sjukdom; funktionsteknik; slumpmässig skog; logistisk regression;

    Abstract : This thesis contains a review of previous work in the fields of encoding sequential healthcare data and predicting graft- versus- host disease, a medical condition, based on patient history using machine learning. A new encoding of such data is proposed for machine learning purposes. READ MORE

  3. 12. Online Anomaly Detection on the Edge

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Marcus Jirwe; [2021]
    Keywords : Predictive maintenance; Anomaly detection; Online learning; Edge environment; Receiver Operating Characteristic curve; Förebyggande underhåll; anomalidetektering; sekventiell inlärning; nätverkskanten; ”Receiver Operating Characterstic”-kurva;

    Abstract : The society of today relies a lot on the industry and the automation of factory tasks is more prevalent than ever before. However, the machines taking on these tasks require maintenance to continue operating. This maintenance is typically given periodically and can be expensive while sometimes requiring expert knowledge. READ MORE

  4. 13. Catch the fraudster : The development of a machine learning based fraud filter

    University essay from Uppsala universitet/Avdelningen för systemteknik

    Author : Anton Andrée; [2020]
    Keywords : fraud: detection: fraud detection: machine learning: filter: fraud filter: random forest: RNN: grey list: gray list: non-numerical: features: fraudulent: banking: ecommerce: transaction;

    Abstract : E-commerce has seen a rapid growth the last two decades, making it easy for customers to shop wherever they are. The growth has also led to new kinds of fraudulent activities affecting the customers. READ MORE

  5. 14. CLASSIFYING TWITTER BOTSA comparasion of methods for classifying whethert weets are written by humans or bots

    University essay from Umeå universitet/Institutionen för datavetenskap

    Author : Simon Västerbo; [2020]
    Keywords : ;

    Abstract : The use of bots to inuence public debate, spread disinformation and spam, creates a need for efficient methods for detecting the usage of bots. This study will compare different machine learning methods in the task of classifying if the author of a tweet is a bot or a human, using tweet level features. READ MORE

  6. 15. Detecting Non-Natural Objects in a Natural Environment using Generative Adversarial Networks with Stereo Data

    University essay from Linköpings universitet/Datorseende

    Author : Nils Gehlin; Martin Antonsson; [2020]
    Keywords : deep learning; anomaly detection; GAN; BergGAN; pGAN; stereo; non-natural objects; natural environment; multi-modal anomaly detection;

    Abstract : This thesis investigates the use of Generative Adversarial Networks (GANs) for detecting images containing non-natural objects in natural environments and if the introduction of stereo data can improve the performance. The state-of-the-art GAN-based anomaly detection method presented by A. Berget al. in [5] (BergGAN) was the base of this thesis. READ MORE