Sökning: "Recursive Feature Elimination"
Visar resultat 1 - 5 av 17 uppsatser innehållade orden Recursive Feature Elimination.
1. RNN-based Graph Neural Network for Credit Load Application leveraging Rejected Customer Cases
Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : Machine learning plays a vital role in preventing financial losses within the banking industry, and still, a lot of state of the art and industry-standard approaches within the field neglect rejected customer information and the potential information that they hold to detect similar risk behavior.This thesis explores the possibility of including this information during training and utilizing transactional history through an LSTM to improve the detection of defaults. LÄS MER
2. Data-Driven Success in Infrastructure Megaprojects. : Leveraging Machine Learning and Expert Insights for Enhanced Prediction and Efficiency
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This Master's thesis utilizes random forest and leave-one-out cross-validation to predict the success of megaprojects involving infrastructure. The goal was to enhance the efficiency of the design and engineering phase of the infrastructure and construction industries. LÄS MER
3. Parkinson’s disease tremor assessment: Leveragingsmartphones for symptom measurement
M1-uppsats, Malmö universitet/Institutionen för datavetenskap och medieteknik (DVMT)Sammanfattning : Parkinson's disease (PD) is a progressive, chronic neurodegenerative disorder that impacts patients' quality of life. Hand tremor is a hallmark motor symptom of PD. However, current clinical tremor assessment methods are time-consuming and expensive and may not capture the full extent of tremor fluctuations. LÄS MER
4. Predicting Workforce in Healthcare : Using Machine Learning Algorithms, Statistical Methods and Swedish Healthcare Data
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : 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. LÄS MER
5. Viewership forecast on a Twitch broadcast : Using machine learning to predict viewers on sponsored Twitch streams
Master-uppsats, Linköpings universitet/Institutionen för datavetenskapSammanfattning : Today, the video game industry is larger than the sports and film industries combined, and the largest streaming platform Twitch with an average of 2.8 million concurrent viewers offers the possibility for gaming and non-gaming brands to market their products. LÄS MER