Essays about: "Boosted Metod"

Showing result 1 - 5 of 8 essays containing the words Boosted Metod.

  1. 1. Recommender Systems Using Limited Dataset Sizes

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

    Author : Carl Bentzer; Harry Thulin; [2023]
    Keywords : ;

    Abstract : In order to create personalized recommendations for users on services such as e-commerce websites and streaming platforms, recommender systems often utilize various machine learning techniques. A common technique used in recommender systems is collaborative filtering which creates rating predictions based on similar users’ interests. READ MORE

  3. 2. Credit Scoring Based on Behavioural Data

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

    Author : Daniel Bouvin; Erik Hamberg; [2022]
    Keywords : Banking; Behavior; Behaviour; Credit Modelling; Klarna; Logistic Regression; Machine Learning; Neural Networks; Random Forests; XGBoost;

    Abstract : Credit modelling has traditionally been done by credit institutes based on financial data about the individuals requesting the credit. While this has been sufficient in lowering risk in developed economies with plenty of financial data it is inefficient in developing economies and fails to reach the unbanked population. READ MORE

  4. 3. Telecommunications Trouble Ticket Resolution Time Modelling with Machine Learning

    University essay from KTH/Matematisk statistik

    Author : Axel Björling; [2021]
    Keywords : Machine learning; regression; classification; telecommunications trouble ticket resolution time; support vector machine; logistic regression; deep neural network; gradient boosted trees regression; Maskininlärning; regression; klassificering; avvikelserapport i telenät; lösningstid felanmälan; support vector machine; logistic regression; neurala nätverk; gradient boosted trees regression;

    Abstract : This report explores whether machine learning methods such as regression and classification can be used with the goal of estimating the resolution time of trouble tickets in a telecommunications network. Historical trouble ticket data from Telenor were used to train different machine learning models. READ MORE

  5. 4. Loss Given Default Estimation with Machine Learning Ensemble Methods

    University essay from KTH/Matematisk statistik

    Author : Elina Velka; [2020]
    Keywords : Loss Given Default; Non-Performing Loans; Internal Ratings Based Approach; Machine Learning; Decision Tree; Random Forest; Boosted Method; Förlust vid fallissemang; Icke-presterande lån; Intern riskklassificeringsmetod; Maskininlärning; Decision Tree; Random Forest; Boosted Metod;

    Abstract : This thesis evaluates the performance of three machine learning methods in prediction of the Loss Given Default (LGD). LGD can be seen as the opposite of the recovery rate, i.e. the ratio of an outstanding loan that the loan issuer would not be able to recover in case the customer would default. READ MORE

  6. 5. Anomaly Detection and Revenue Loss Estimation in Accounting Data

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

    Author : Gustav Edholm; [2020]
    Keywords : Machine Learning; Anomaly Detection; Regression; Neural Network; Invoice; Revenue Loss; Maskininlärning; Avvikelsedetektion; Regression; Neuralnät; Faktura; Omsättningsförlust;

    Abstract : Loss of revenue due to erroneous invoicing is a serious problem for many companies in the repair and maintenance industry. Revenue loss can occur in many ways, for example by consistently charging the wrong hourly price for services. READ MORE