Essays about: "random forest klassificerare"

Showing result 1 - 5 of 8 essays containing the words random forest klassificerare.

  1. 1. Eye Movement Analysis for Activity Recognition in Everyday Situations

    University essay from Malmö universitet/Teknik och samhälle

    Author : Anton Gustafsson; [2018]
    Keywords : activity recognition; artificial intelligence; data annotation; eye tracking; eye movement analysis; gaze tracking; human activity recognition; intention recognition; machine learning;

    Abstract : Den ständigt ökande mängden av smarta enheter i vår vardag har lett till nya problem inom HCI så som hur vi människor ska interagera med dessa enheter på ett effektivt och enkelt sätt. Än så länge har kontextuellt medvetna system visat sig kunna vara ett möjligt sätt att lösa detta problem. READ MORE

  2. 2. Post-Pruning of Random Forests

    University essay from Blekinge Tekniska Högskola/Institutionen för datalogi och datorsystemteknik

    Author : Jamal Diyar; [2018]
    Keywords : Random Forests; pruning; interpretability; accuracy.;

    Abstract : Abstract  Context. In machine learning, ensemble methods continue to receive increased attention. Since machine learning approaches that generate a single classifier or predictor have shown limited capabilities in some contexts, ensemble methods are used to yield better predictive performance. READ MORE

  3. 3. Detection of Web API Content Scraping : An Empirical Study of Machine Learning Algorithms

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

    Author : Dina Jawad; [2017]
    Keywords : web API; scraping; machine learning; supervised learning; web API content scraping;

    Abstract : Scraping is known to be difficult to detect and prevent, especially in the context of web APIs. It is in the interest of organisations that rely heavily on the content they provide through their web APIs to protect their content from scrapers. In this thesis, a machine learning approach towards detecting web API content scrapers is proposed. READ MORE

  4. 4. A Machine Learning Ensemble Approach to Churn Prediction : Developing and Comparing Local Explanation Models on Top of a Black-Box Classifier

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

    Author : Nina Olofsson; [2017]
    Keywords : Machine learning; Ensemble; Random forest; Churn prediction; LIME; Interpretability; CRM; Local explanations;

    Abstract : Churn prediction methods are widely used in Customer Relationship Management and have proven to be valuable for retaining customers. To obtain a high predictive performance, recent studies rely on increasingly complex machine learning methods, such as ensemble or hybrid models. READ MORE

  5. 5. A Hybrid Film Recommender System Based on Random Forest : Designing for simplicity and how it affects performance

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

    Author : Andreas Brommund; David Skeppstedt; [2017]
    Keywords : ;

    Abstract : Thanks to the internet an abundance of information is available just one click away. All this information is difficult to digest. Thus, a lot of time has been devoted to research how to build powerful and efficient information filtering systems. READ MORE