Sökning: "Bayesian network"
Visar resultat 1 - 5 av 69 uppsatser innehållade orden Bayesian network.
1. Machine Learning for a Network-based Intrusion Detection System : An application using Zeek and the CICIDS2017 datasetM1-uppsats, KTH/Hälsoinformatik och logistik
Sammanfattning : Cyber security is an emerging ﬁeld in the IT-sector. As more devices are connected to the internet, the attack surface for hackers is steadily increasing. Network-based Intrusion Detection Systems (NIDS) can be used to detect malicious traﬃc in networks and Machine Learning is an up and coming approach for improving the detection rate. LÄS MER
- Master-uppsats, KTH/Matematisk statistik
Sammanfattning : Smart Meters are measuring devices collecting labeled time series data of utility consumptions from sub-meters and are capable of automatically transmit-ting this between the customer and utility companies together with other companies that offer services such as monitoring of consumption and cleaning of data. The smart meters are in some cases experiencing communication errors. LÄS MER
3. Classification of Wi-Fi Sensor Data for a Smarter City : Probabilistic Classification using Bayesian StatisticsUppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik; Umeå universitet/Institutionen för matematik och matematisk statistik
Sammanfattning : As cities are growing with an increasing number of residents, problems with the traffic such as congestion and larger emission arise. The city planners have challenges with making it as easy as possible for the residents to commute and in as large scale as possible to avoid vehicles. LÄS MER
- Master-uppsats, Uppsala universitet/Statistiska institutionen
Sammanfattning : Obesity is a growing problem globally. Currently 2.3 billion adults are overweight, and this number is rising. The most common method for weight loss is calorie counting, in which to lose weight a person should be in a calorie deficit. LÄS MER
- Magister-uppsats, Umeå universitet/Statistik
Sammanfattning : Bayesian Network (BN) classifiers are a type of probabilistic models. The learning process consists of two steps, structure learning and parameter learning. Four BN classifiers will be learned. These are two different Naive Bayes classifiers (NB), one Tree Augmented Naive Bayes classifier (TAN) and one Forest Naive Bayes classifier (FAN). LÄS MER