Sökning: "Scikit-Learn"

Visar resultat 11 - 15 av 27 uppsatser innehållade ordet Scikit-Learn.

1. 11. A Comparative Study of Facial Recognition Techniques : With focus on low computational power

   Kandidat-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi

   Författare :Timmy Schenkel; Oliver Ringhage; Nicklas Branding; [2019]
   Nyckelord :Machine Learning; Facial Recognition; Low Computational Power;

   Sammanfattning : Facial recognition is an increasingly popular security measure in scenarios with low computational power, such as phones and Raspberry Pi’s. There are many facial recognition techniques available. The aim is to compare three such techniques in both performance and time metrics. LÄS MER

3. 12. Predicting house prices with machine learning methods

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

   Författare :Isak Engström; Alan Ihre; [2019]
   Nyckelord :;

   Sammanfattning : In this study, the machine learning algorithms k-Nearest-Neighbours regression (k-NN) and Random Forest (RF) regression were used to predict house prices from a set of features in the Ames housing data set. The algorithms were selected from an assessment of previous research and the intent was to compare their relative performance at this task. LÄS MER

4. 13. Machine Learning for a Network-based Intrusion Detection System : An application using Zeek and the CICIDS2017 dataset

   M1-uppsats, KTH/Hälsoinformatik och logistik

   Författare :Vilhelm Gustavsson; [2019]
   Nyckelord :Machine Learning; Flow-based traffic characterization; Intrusion Detection System IDS ; Zeek; Bro; CICIDS2017; Scikit-Learn; Maskininlärning; Flödesbaserad trafik-karaktärisering; Intrångsdetekteringssystem IDS ; Zeek; Bro; CICIDS2017; Scikit-Learn;

   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

5. 14. A comparative study of social bot classification techniques

   Kandidat-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi

   Författare :Filip Örnbratt; Jonathan Isaksson; Mario Willing; [2019]
   Nyckelord :manual bot classification; social bot; metadata; machine learning; supervised learning; unsupervised learning; random forest; k-means;

   Sammanfattning : With social media rising in popularity over the recent years, new so called social bots are infiltrating by spamming and manipulating people all over the world. Many different methods have been presented to solve this problem with varying success. LÄS MER

7. 15. Att förutspå Sveriges bistånd : En jämförelse mellan Support Vector Regression och ARIMA

   Kandidat-uppsats, Mittuniversitetet/Institutionen för informationssystem och –teknologi

   Författare :Max Wågberg; [2019]
   Nyckelord :Machine-learning; Python; ARIMA; SVR; Timeseries; Regression; Maskininlärning; Python; ARIMA; SVR; Tidsserie; Regression;

   Sammanfattning : In recent years, the use of machine learning has increased significantly. Its uses range from making the everyday life easier with voice-guided smart devices to image recognition, or predicting the stock market. Predicting economic values has long been possible by using methods other than machine learning, such as statistical algorithms. LÄS MER