Essays about: "EXAMPLE OF CLASSIFICATION"

Showing result 6 - 10 of 190 essays containing the words EXAMPLE OF CLASSIFICATION.

  1. 6. EU Taxonomy from the Perspective of Investors

    University essay from Linköpings universitet/Industriell miljöteknik

    Author : Agnes Isaksson; Ismira Hodžić; [2023]
    Keywords : EU Taxonomy; Investors; Investment Decisions; Sustainable Investments; Sustainability Reporting; SFDR; CSRD; Asymmetric Information; Legitimacy Theory;

    Abstract : To redirect capital flows towards sustainable investments, the European Union (EU) has implemented the EU Taxonomy, a classification system with definitions for sustainable economic activities. The Taxonomy constitutes a part of the European Green Deal, which is an initiative to transition the EU towards sustainability and competitiveness. READ MORE

  3. 7. Developing an Advanced Method for Kinship from Ancient DNA Data

    University essay from Uppsala universitet/Institutionen för biologisk grundutbildning

    Author : Erkin Alacamli; [2023]
    Keywords : aDNA; ancient DNA; kinship estimation;

    Abstract :  The analysis of kinship from ancient DNA (aDNA) data has the potential to provide insight into social structures of prehistoric societies. Kinship analysis is gaining popularity as optimised wet-lab methods allow for studies with sample sizes on the level of whole cemeteries. READ MORE

  4. 8. Automatic Analysis of Peer Feedback using Machine Learning and Explainable Artificial Intelligence

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

    Author : Kevin Huang; [2023]
    Keywords : Text classification; Peer feedback; Explainable Artificial Intelligence; BERT; RoBERTa; DistilBERT; Decision Tree; MLP; CSCL; STEM education; Textklassificering; Feedback till kamrater; Förklarig Artificiell Intelligens; BERT; RoBERTa; DistilBERT; Decision Tree; MLP; CSCL; STEM-utbildning;

    Abstract : Peer assessment is a process where learners evaluate and provide feedback on one another’s performance, which is critical to the student learning process. Earlier research has shown that it can improve student learning outcomes in various settings, including the setting of engineering education, in which collaborative teaching and learning activities are common. READ MORE

  5. 9. Quantum Algorithms for Feature Selection and Compressed Feature Representation of Data

    University essay from KTH/Fysik

    Author : William Laius Lundgren; [2023]
    Keywords : Feature selection; autoencoders; quantum machine learning; quantum circuits; quantum annealing; Funktionsval; datakompression; kvantmaskininlärning; kvantalgoritmer; kvantkretsar;

    Abstract : Quantum computing has emerged as a new field that may have the potential to revolutionize the landscape of information processing and computational power, although physically constructing quantum hardware has proven difficult,and quantum computers in the current Noisy Intermediate Scale Quantum (NISQ) era are error prone and limited in the number of qubits they contain.A sub-field within quantum algorithms research which holds potential for the NISQ era, and which has seen increasing activity in recent years, is quantum machine learning, where researchers apply approaches from classical machine learning to quantum computing algorithms and explore the interplay between the two. READ MORE

  6. 10. Evaluating Random Forest and k-Nearest Neighbour Algorithms on Real-Life Data Sets

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

    Author : Atheer Salim; Milad Farahani; [2023]
    Keywords : Random Forest; k-Nearest Neighbour; Evaluation; Machine Learning; Classification; Execution Time; Slumpmässig Skog; k-Närmaste Granne; Utvärdering; Maskininlärning; Klassificiering; Exekveringstid;

    Abstract : Computers can be used to classify various types of data, for example to filter email messages, detect computer viruses, detect diseases, etc. This thesis explores two classification algorithms, random forest and k-nearest neighbour, to understand how accurately and how quickly they classify data. READ MORE