Sökning: "Bias in Machine Learning"
Visar resultat 1 - 5 av 76 uppsatser innehållade orden Bias in Machine Learning.
1. On The Evaluation of District Heating Load Predictions
Master-uppsats, Lunds universitet/Institutionen för energivetenskaperSammanfattning : District Heating is a technology with the potential to enable a fossil-free society. However, to realize this potential, some improvements need to be made in order to improve District Heating operation at large, decrease losses in the systems, and thus increase the competitiveness of District Heating as a technology. LÄS MER
2. The dark side of AI : A systematic literature review
Magister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : The world is currently experiencing an extraordinary explosion of data due to the advancements in digitalization, this has made the decision-making processes become increasingly complex. Modern decision-making incorporates various technologies such as AI, big data, and machine learning and they offer significant advantages in terms of speed, scalability, and granularity. LÄS MER
3. Gender Bias in Machine Learning : The Effect of Using Female Versus Male Audio When Classifying Emotions in Speech Using Machine Learning
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : To avoid discrimination between the genders and to improve the performance of machine learning, it is important to evaluate how different test data can impact how accurate machine learning models can be. This study investigates if the distribution between women and men in the training data affects how accurately different machine learning models can classify emotions used in the speaker’s tone of voice. LÄS MER
4. Double Machine Learning for Insurance Price Optimization
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)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
5. A deep learning approach for drilling tool condition monitoring in Raiseboring
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : Drilling tool wear can significantly affect the performance of the drilling operation and add extra cost to it. Accurate detection of drilling tool condition is very important for enabling proactive maintenance, minimizing downtime, and optimizing drilling processes. LÄS MER