Sökning: "Semi-supervised learning"
Visar resultat 1 - 5 av 18 uppsatser innehållade orden Semi-supervised learning.
- Master-uppsats, KTH/Robotik, perception och lärande, RPL
Sammanfattning : This project focuses on semi-supervised human activity recognition (HAR) tasks, in which the inputs are partly labeled time series data acquired from sensors such as accelerometer data, and the outputs are predefined human activities. Most state-of-the-art existing work in HAR area is supervised now, which relies on fully labeled datasets. LÄS MER
2. Exploit Unlabeled Data with Language Model for Text Classification. Comparison of four unsupervised learning modelsMaster-uppsats, Göteborgs universitet/Institutionen för filosofi, lingvistikoch vetenskapsteori
Sammanfattning : Within a situation where Semi-Supervised Learning (SSL) is available to exploit unlabeled data, this paper shows that Language Model (LM) outperforms the three models in text classification, which three models are based on Term-Frequency Inverse Document Frequency (Tf-idf) and two pre-trained word vectors. The experimental results show that the LM outperforms the other three unsupervised learning models whether the task is easy or difficult, which the difficult task consists of imbalanced data. LÄS MER
- Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : The goal of this master’s thesis was to create a model that predicts preference towards a specific exclusive feature in a subscribed service. It investigated unsupervised and semi-supervised learning to identify customer segments that prefer an specific exclusive feature. LÄS MER
- Master-uppsats, Uppsala universitet/Statistiska institutionen
Sammanfattning : Given the explosion in the size of social media, the amount of hate speech is also growing. To efficiently combat this issue we need reliable and scalable machine learning models. Current solutions rely on crowdsourced datasets that are limited in size, or using training data from self-identified hateful communities, that lacks specificity. LÄS MER
- Kandidat-uppsats, Stockholms universitet/Avdelningen för datorlingvistik
Sammanfattning : Automatic morpheme segmentation as a field has been dominated by unsupervised methods since its inception. Partly due to theoretical motivations, but also due to resource constraints. LÄS MER