Essays about: "random forest klassificerare"

Showing result 6 - 10 of 36 essays containing the words random forest klassificerare.

  1. 6. Textual Analysis and Detection of AIGenerated Academic Texts : A Study of ChatGPT Output, User Instructions, and Machine-Learning Classifiers

    University essay from Mittuniversitetet/Institutionen för data- och elektroteknik (2023-)

    Author : Adnan Al Medawer; [2023]
    Keywords : AI-generated texts; ChatGPT; Machine-learning; Text characteristics; Language models; Text Analysis; Detection tool.; AI-genererade texter; ChatGPT; Maskininlärning; Textegenskaper; Språkmodeller; Textanalys; AI-Detektion Verktyg;

    Abstract : Den här studien utforskar den textmässiga likheten mellan AI-genererade texter av ChatGPT och ursprungliga akademiska texter, jämför prestandan hos AI-detekteringsverktyg och maskininlärningsklassificerare, inklusive SVM, Logistic Regression och Random Forest, vid detektering av AI-genererat innehåll, och undersöker hur användarinstruktioner påverkar textkvaliteten. En rad mätvärden som stilometri, sentiment, textlikhet, läsbarhet och relevans användes för att analysera textegenskaper. READ MORE

  3. 7. Classification of imbalanced disparate medical data using ontology

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

    Author : Ludvig Karlsson; Gustav Wilhelm Kopp Sundin; [2023]
    Keywords : Ontology; machine learning; random forest; imbalanced data; oncology; digital transformation;

    Abstract : Through the digitization of healthcare, large volumes of data are generated and stored in healthcare operations. Today, a multitude of platforms and digital infrastructures are used for storage and management of data. The systems lack a common ontology which limits the interoperability between datasets. READ MORE

  4. 8. Machine Learning Algorithms to Predict Cost Account Codes in an ERP System : An Exploratory Case Study

    University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Author : Alexander Wirdemo; [2023]
    Keywords : Artificial Intelligence; Machine Learning; ERP; invoice automation; RPA; Random forest; Naïve Bayes; k-Nearest Neighbor; Artificiell Intelligens; maskinlärning; ERP; fakturaautomation; RPA; Random forest; Naïve Bayes; k-Nearest Neighbor;

    Abstract : This study aimed to investigate how Machine Learning (ML) algorithms can be used to predict the cost account code to be used when handling invoices in an Enterprise Resource Planning (ERP) system commonly found in the Swedish public sector. This implied testing which one of the tested algorithms that performs the best and what criteria that need to be met in order to perform the best. READ MORE

  5. 9. A Comparative Study on the Effects of Removing the Most Important Feature on Random Forest and Support Vector Machine

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

    Author : Henrik Åkesson; Hampus Fridlund; [2023]
    Keywords : ;

    Abstract : Machine learning (ML) for classification is largely regarded as a “black box”, in that it’s difficult to fully understand how the model reached a decision, and how changes to the input affects the output. Therefore, exploring the inner workings of classification models are of interest for expanding the current knowledge base, providing guidelines for choosing a more suitable classification model for a specific problem. READ MORE

  6. 10. Machine Learning for Improving Detection of Cooling Complications : A case study

    University essay from KTH/Industriell produktion

    Author : William Bruksås Nybjörk; [2022]
    Keywords : Temperature controllable containers; Machine Learning; imbalanced data; data analysis; noisy labels; feature engineering; threshold tuning;

    Abstract : The growing market for cold chain pharmaceuticals requires reliable and flexible logistics solutions that ensure the quality of the drugs. These pharmaceuticals must maintain cool to retain the function and effect. Therefore, it is of greatest concern to keep these drugs within the specified temperature interval. READ MORE