Sökning: "Tolkningsbar Maskininlärning"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden Tolkningsbar Maskininlärning.

1. 1. Zero/Few-Shot Text Classification : A Study of Practical Aspects and Applications

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Jacob Åslund; [2021]
   Nyckelord :zero-shot learning; few-shot learning; text classification; active learning; automated data labeling; interpretable machine learning; deep learning; NLP; NLU; zero-shot learning; few-shot learning; textklassificering; aktiv inlärning; automatiserad datamärkning; tolkningsbar maskininlärning; djupinlärning; NLP; NLU;

   Sammanfattning : SOTA language models have demonstrated remarkable capabilities in tackling NLP tasks they have not been explicitly trained on – given a few demonstrations of the task (few-shot learning), or even none at all (zero-shot learning). The purpose of this Master’s thesis has been to investigate practical aspects and potential applications of zero/few-shot learning in the context of text classification. LÄS MER

3. 2. Hybrid Ensemble Methods: Interpretible Machine Learning for High Risk Aeras

   Master-uppsats, KTH/Matematisk statistik

   Författare :Maria Ulvklo; [2021]
   Nyckelord :Interpretability; Machine Learning; Sparse Data; Ensemble; Cyber Security; High Risk Sectors; Tolkbarhet; Maskininlärning; Gles Data; Ensemblemetoder; Cybersäkerhet; Högriskområden;

   Sammanfattning : Despite the access to enormous amounts of data, there is a holdback in the usage of machine learning in the Cyber Security field due to the lack of interpretability of ”Black­box” models and due to heterogenerous data. This project presents a method that provide insights in the decision making process in Cyber Security classification. LÄS MER

4. 3. On the impact of geospatial features in real estate appraisal with interpretable algorithms

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Simon Jäger; [2021]
   Nyckelord :Geospatial Features; Interpretable Artificial Intelligence; Feature Importance; Real Estate Appraisal; Geospatiala Variabler; Tolkningsbar Artificiell Intelligens; Variabelbetydelse; Fastighetsvärdering;

   Sammanfattning : Real estate appraisal is the means of defining the market value of land and property affixed to it. Many different features determine the market value of a property. For example, the distance to the nearest park or the travel time to the central business district may be significant when determining its market value. LÄS MER

5. 4. Assessment of Predictive Models for Improving Default Settings in Streaming Services

   M1-uppsats, KTH/Skolan för kemi, bioteknologi och hälsa (CBH)

   Författare :Mouzeina Lattouf; [2020]
   Nyckelord :Interpretable Machine Learning; Machine Learning; Shapley Additive Explanations; User Settings; User experience; Användarinställningar; Användarupplevelse; Maskininlärning; Shapley Additive Explanations; Tolkningsbar Maskininlärning;

   Sammanfattning : Streaming services provide different settings where customers can choose a sound and video quality based on personal preference. The majority of users never make an active choice; instead, they get a default quality setting which is chosen automatically for them based on some parameters, like internet connection quality. LÄS MER

7. 5. A MODEL-INDEPENDENT METHODOLOGY FOR A ROOT CAUSE ANALYSIS SYSTEM : A STUDY INVESTIGATING INTERPRETABLE MACHINE LEARNING METHODS

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Emil Conradsson; Vidar Johansson; [2019]
   Nyckelord :;

   Sammanfattning : Today, companies like Volvo GTO experience a vast increase in data and the ability toprocess it. This makes it possible to utilize machine learning models to construct a rootcause analysis system in order to predict, explain and prevent defects. LÄS MER