Essays about: "Predicering"

Showing result 1 - 5 of 10 essays containing the word Predicering.

  1. 1. Predicting Patent Data using Wavelet Regression and Bayesian Machine Learning

    University essay from KTH/Matematik (Avd.)

    Author : Mattias Martinsen; [2023]
    Keywords : Wavelet; Regression; Bayesian network; Prediction; Patent; Machine Learning; Wavelet; Regression; Bayesiskt nätverk; Predicering; Patent; Maskininlärning;

    Abstract : Patents are a fundamental part of scientific and engineering work, ensuringprotection of inventions owned by individuals or organizations. Patents areusually made public 18 months after being filed to a patent office, whichmeans that current publicly available patent data only provides informationabout the past. READ MORE

  3. 2. The Impact of the Retrieval Text Set for Text Sentiment Classification With the Retrieval-Augmented Language Model REALM

    University essay from KTH/Matematik (Inst.)

    Author : Oscar Blommegård; [2023]
    Keywords : The Impact of the Retrieval Text Set for Text Sentiment Classification With the Retrieval-Augmented Language Model REALM; Hämtningsförstärkta språkmodeller; Natural Language Processing; Transformers; Djupinlärning; Textklassificering;

    Abstract : Large Language Models (LLMs) have demonstrated impressive results across various language technology tasks. By training on large corpora of diverse text collections from the internet, these models learn to process text effectively, allowing them to acquire comprehensive world knowledge. READ MORE

  4. 3. Predicting Equity Fund Returns: The Impact of the Momentum-Factor on Performance

    University essay from KTH/Matematisk statistik

    Author : Pontus Hovberger; Hugo Brunlid; [2023]
    Keywords : Equity Funds; Value; Growth; Momentum; Carhart Four-Factor Model; Multifactor Model; Momentum Crashes; Aktiefonder; Värdeaktier; Tillväxtaktier; Momentum; Carhart Four-Factor Model; Multifaktormodell; Momentumkrascher;

    Abstract : Momentum has been a persistent and robust factor in explaining excess future returns, generating great interest from investors and financial analysts. Following the financial crisis of 2008 and the Covid-19 pandemic, there have been instances of significant momentum crashes. READ MORE

  5. 4. Predicting Workforce in Healthcare : Using Machine Learning Algorithms, Statistical Methods and Swedish Healthcare Data

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

    Author : Gabriel Diskay; Carl Joelsson; [2023]
    Keywords : Machine Learning ML ; Linear Regression Model LRM ; Gradient Boosting Regressor GBR ; Exponential Smoothing Model ESM ; Workforce Prediction WP ; Healthcare Sector HS ; Labor Policy LP ; Beveridge Curve BC ; Economic Forecasting EF ; Recursive Feature Elimination RFE ; Human Resource Management HRM ;

    Abstract : Denna studie undersöker användningen av maskininlärningsmodeller för att predicera arbetskraftstrender inom hälso- och sjukvården i Sverige. Med hjälp av en linjär regressionmodell, en Gradient Boosting Regressor-modell och en Exponential Smoothing-modell syftar forskningen för detta arbete till att ge viktiga insikter för underlaget till makroekonomiska överväganden och att ge en djupare förståelse av Beveridge-kurvan i ett sammanhang relaterat till hälso- och sjukvårdssektorn. READ MORE

  6. 5. Time Series Analysis and Binary Classification in a Car-Sharing Service : Application of data-driven methods for analysing trends, seasonality, residuals and prediction of user demand

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

    Author : Aksel Uhr; [2023]
    Keywords : Smart mobility; Car-sharing; Time series analysis; Demand prediction; Machine learning; Supervised learning; Binary classification; Random forest; Smart mobilitet; Bildelning; Tidsseriaanalys; Efterfrågansprediktering; Maskininlärning; Väglett lärande; Binär klassificering; Slumpmässiga skogar;

    Abstract : Researchers have estimated a 20-percentage point increase in the world’s population residing in urban areas between 2011 and 2050. The increase in denser cities results in opportunities and challenges. Two of the challenges concern sustainability and mobility. READ MORE