Sökning: "Datamängd"

Visar resultat 1 - 5 av 237 uppsatser innehållade ordet Datamängd.

1. 1. Decision Trees for Classification of Repeated Measurements

   Kandidat-uppsats, Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakulteten

   Författare :Julianna Holmberg; [2024]
   Nyckelord :Repeated Measurement Data; Growth Curve Model; Linear Discriminant Analysis; Decision Tree; Bootstrap Aggregating; CART; CART-LC;

   Sammanfattning : Classification of data from repeated measurements is useful in various disciplines, for example that of medicine. This thesis explores how classification trees (CART) can be used for classifying repeated measures data. LÄS MER

3. 2. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning

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

   Författare :Khalid El Yaacoub; [2024]
   Nyckelord :Sustainable AI; Machine learning; Quantization-Aware Training; Model Distillation; Quantized Distillation; Siamese Neural Networks; Continual Learning; Experience Replay; Data Efficient AI; Energy Consumption; Energy-Savings; Sustainable ML; Computation resources; Hållbar maskin inlärning; Hållbar AI; Maskininlärning; Quantization-Aware Training; Model Distillation; Quantized Distillation; siamesiska neurala nätverk; Continual Learning; Experience Replay; Dataeffektiv AI; Energiförbrukning; Energibesparingar; Beräkningsresurser;

   Sammanfattning : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. LÄS MER

4. 3. Machine Learning model applied to Reactor Dynamics

   Master-uppsats, KTH/Fysik

   Författare :Dionysios Dimitrios Nikitopoulos; [2023]
   Nyckelord :Master Thesis; Machine Learning; stability; Energy distribution profiles; Prediction; frequency; decay ratio; Data processing; POLCA-T; Pytorch; testing data; RMSE. ii;

   Sammanfattning : This project’s idea revolved around utilizing the most recent techniques in MachineLearning, Neural Networks, and Data processing to construct a model to be used asa tool to determine stability during core design work. This goal will be achieved bycollecting distribution profiles describing the core state from different steady statesin five burn-up cycles in a reactor to serve as the dataset for training the model. LÄS MER

5. 4. Double Machine Learning for Insurance Price Optimization

   Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

   Författare :Jakob Kristiansson; [2023]
   Nyckelord :DML; Double Machine Learning; Price Optimization; Insurance Pricing; DML; Dubbel Maskininlärning; Prisoptimering; Försäkringsprissättning;

   Sammanfattning : This thesis examines how recent advances in debaised machine learning can be used for estimating price elasticities of demand within the automotive insurance field. Traditional methods such as generalized linear model (GLM) to estimate demand has no way of ensuring there are no biases in the underlying data selection, especially when the confounding variables are many. LÄS MER

7. 5. Performance of the relational and non-relational databases

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

   Författare :Ahmed Alkhalaf; Hasan Al-Zubeidi; [2023]
   Nyckelord :Databases Management System; Relational Databases; Non-relational Databases; Number of Records; Databashanteringssystem; Relationsdatabaser; Icke-relationella databaser; Datamängd;

   Sammanfattning : There are many types of databases, but the most common are relational and non-relational. These databases have different structures, and that affects their performance. Many studies examine the differences between relational and non-relational databases and compare them regarding performance. LÄS MER