Sökning: "Övervakad inlärning"

Visar resultat 1 - 5 av 63 uppsatser innehållade orden Övervakad inlärning.

1. 1. Analyzing How Blended Emotions are Expressed using Machine Learning Methods

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

   Författare :Disen Ling; [2023]
   Nyckelord :Blended emotion; Supervised learning; Model generalization capability; Ablation study; Blandade känslor; Övervakad inlärning; Modellens generaliseringsförmåga; Ablationsstudie;

   Sammanfattning : Blended emotion is a classification of emotional experiences that involve the combination of multiple emotions. Research on the expression of blended emotions allows researchers to understand how different emotions interact and coexist in an individual’s emotional experience. LÄS MER

3. 2. Classification of Radar Emitters using Semi-Supervised Contrastive Learning

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

   Författare :Tim Jonsson; [2023]
   Nyckelord :;

   Sammanfattning : Radar is a commonly used radio equipment in military and civilian settings for discovering and locating foreign objects. In a military context, pilots being discovered by radar could have fatal consequences. LÄS MER

4. 3. Supervised Failure Diagnosis of Clustered Logs from Microservice Tests

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

   Författare :Amanda Strömdahl; [2023]
   Nyckelord :Supervised Learning; Failure Diagnosis; Clustered Log Data; Random Forest; SVM; MLP; Övervakad inlärning; feldiagnos; klustrad logg-data; Random Forest; SVM; MLP;

   Sammanfattning : Pinpointing the source of a software failure based on log files can be a time consuming process. Automated log analysis tools are meant to streamline such processes, and can be used for tasks like failure diagnosis. This thesis evaluates three supervised models for failure diagnosis of clustered log data. LÄS MER

5. 4. Evaluating machine learning models for time series forecasting in smart buildings

   M1-uppsats, KTH/Hälsoinformatik och logistik

   Författare :Sarugan Balachandran; Diego Perez Legrand; [2023]
   Nyckelord :Machine learning; supervised learning; time series forecasting; neural networks; LSTM; En- semble LSTM; AT-LSTM; ARIMA; XGBoost; Maskininlärning; övervakad inlärning; tidsserie-prognostisering; neurala nätverk; LSTM; En- semble LSTM; AT-LSTM; ARIMA; XGBoost;

   Sammanfattning : Temperature regulation in buildings can be tricky and expensive. A common problem when heating buildings is that an unnecessary amount of energy is supplied. This waste of energy is often caused by a faulty regulation system. LÄS MER

7. 5. Anomaly detection for prediction of failures in manufacturing environments : Machine learning based semi-supervised anomaly detection for multivariate time series to predict failures in a CNC-machine

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

   Författare :Felix Boltshauser; [2023]
   Nyckelord :Machine learning; Anomaly Detection; DeepAnT; ROCKET; OCSVM; manufacturing; predictive maintenance; Maskin inlärning; Anomali Detektion; DeepAnT; ROCKET; OCSVM; tillverkning; prediktivt underhåll;

   Sammanfattning : For manufacturing enterprises, the potential of collecting large amounts of data from production processes has enabled the usage of machine learning for prediction-based monitoring and maintenance of machines. Yet common maintenance strategies still include reactive handling of machine failures or schedule-based maintenance conducted by experienced personnel. LÄS MER