Sökning: "machine learning"
Visar resultat 16 - 20 av 1651 uppsatser innehållade orden machine learning.
- Master-uppsats, KTH/Matematisk statistik; KTH/Matematisk statistik
Sammanfattning : The desire to model the true gain from targeting an individual in marketing purposes has lead to the common use of uplift modeling. Uplift modeling requires the existence of a treatment group as well as a control group and the objective hence becomes estimating the difference between the success probabilities in the two groups. LÄS MER
- Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik
Sammanfattning : Timings at future controls in Vasaloppet were predicted using timings at past and current controls. Predictions were made using linear regression, deep neural networks and support vector machine regression. Timings up to the current control and age were used as input data; predicted timing at a future control was used as output data. LÄS MER
18. Deep Learning and Image Processingfor Handwritten Style Recognition : Deep Learning and Image Processingfor Handwritten Style RecognitionMaster-uppsats, Uppsala universitet/Institutionen för informationsteknologi
Sammanfattning : Medieval manuscripts provide insights into our history. Understanding and analyzing medieval scripts usually require experienced paleographers. Recognizing handwritten styles from medieval scripts provides better insights into understanding of medieval manuscripts. LÄS MER
- Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap
Sammanfattning : Background: With savvier management teams, airlines are becoming more stable, more productive, and more profitable. The problems plaguing the aviation industry, however, have not gone away and have become more complicated instead. Schedule recovery is the process of recovery from these issues (also known as operating disturbances). LÄS MER
20. Predicering av låntagares återbetalningsförmåga med hjälp av maskininlärningsmetoder : En jämförelse av metoderna logistisk regression, random forest, K-nearest neighbor och support vector machinesKandidat-uppsats, Uppsala universitet/Statistiska institutionen; Uppsala universitet/Statistiska institutionen
Sammanfattning : This thesis aims to investigate how statistical machine learning methods can be used to predict an individual's risk of default with regards to chosen model evaluation parameters. Logistic regression, random forest, K-nearest neighbor and support vector machines were the investigated techniques. LÄS MER