Essays about: "Relevance Vector Machines"

Found 3 essays containing the words Relevance Vector Machines.

  1. 1. Machine Learning for Market Prediction : Soft Margin Classifiers for Predicting the Sign of Return on Financial Assets

    University essay from Linköpings universitet/Produktionsekonomi

    Author : George Abo Al Ahad; Abbas Salami; [2018]
    Keywords : Machine Learning; Finance; Financial Time Series; Support Vector Machines; Relevance Vector Machines; Multiple Kernel Learning; Simulated Annealing; SVM; RVM; MKL; SA; FSVM; TSVM; FTSVM;

    Abstract : Forecasting procedures have found applications in a wide variety of areas within finance and have further shown to be one of the most challenging areas of finance. Having an immense variety of economic data, stakeholders aim to understand the current and future state of the market. READ MORE

  3. 2. Relevance classification of connected vehicles for short-lived distributed geospatial events

    University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)

    Author : William Perkola; [2017]
    Keywords : ;

    Abstract : Continuously increasing connectivity of today’s road vehicles has made communication between road vehicles and the outside world more accessible and easier to handle, which has resulted in newly identified areas of improvement regarding road safety and traffic efficiency. Such an area concerns informing road vehicles about ongoing events in the spatial road network near road vehicles and the problem of determining for which road vehicles such information is relevant in an efficient manner. READ MORE

  4. 3. Classification of Hate Tweets and Their Reasons using SVM

    University essay from Uppsala universitet/Avdelningen för datalogi

    Author : Natalya Tarasova; [2016]
    Keywords : Support Vector Machines; classification; Akaike Information Criteria; machine learning; Twitter; hate tweets;

    Abstract : Denna studie fokuserar på att klassificera hat-meddelanden riktade mot mobiloperatörerna Verizon,  AT&T and Sprint. Huvudsyftet är att med hjälp av maskininlärningsalgoritmen Support Vector Machines (SVM) klassificera meddelanden i fyra kategorier - Hat, Orsak, Explicit och Övrigt - för att kunna identifiera ett hat-meddelande och dess orsak. READ MORE