Essays about: "Supervised learning by classification"

Showing result 1 - 5 of 115 essays containing the words Supervised learning by classification.

  1. 1. Cooperative security log analysis using machine learning : Analyzing different approaches to log featurization and classification

    University essay from Linköpings universitet/Databas och informationsteknik

    Author : Fredrik Malmfors; [2022]
    Keywords : Machine learning; word embeddings; deep learning; LSTM; CNN; auto encoder; NLP; natural language processing; intrusion detection; log analysis; logs; log classification; anomaly detection; supervised learning; unsupervised learning;

    Abstract : This thesis evaluates the performance of different machine learning approaches to log classification based on a dataset derived from simulating intrusive behavior towards an enterprise web application. The first experiment consists of performing attacks towards the web app in correlation with the logs to create a labeled dataset. READ MORE

  2. 2. Predicting purchase intentions of customers by using web data : To identify potential customer groups during sales processes in the real estate sector

    University essay from Uppsala universitet/Avdelningen för systemteknik

    Author : Olle Kåhre Zäll; [2022]
    Keywords : Web Usage Mining; Classification; Purchase Intentions; Time On the Market;

    Abstract : This master thesis aims to investigate the possibilities of predicting purchase intentions of customers during their sales processes in the real estate sector. Also, the web activity of customers on a real estate company’s web site is used as the basis for the forecasting. READ MORE

  3. 3. Carta ex Machina: Testing object-based machine learning and unsupervised classification in land use change detection mapping in the semi-arid governorate of Sidi Bouzid, Tunisia

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Kristian Emil Havnsgaard Paludan; [2021]
    Keywords : Change detection; Land use mapping; LANDSAT MSS; LANDSAT TM; GEOBIA; Random Forest classification; ISODATA cluster classification; Object-based classification; Semi-arid agriculture; Irrigation mapping; Earth and Environmental Sciences;

    Abstract : Sidi Bouzid, Tunisia is an inland governorate in Tunisia that has undergone a rapid agricultural and urban development since the Tunisian independence in 1952 from being a rural and largely nomadic region into a hub of irrigated agriculture. In 2010 Mohamed Bouazizi sparked the Tunisian revolution by lighting himself on fire int he city of Sidi Bouzid, with some blaming the inequality and water scarcity created by this rapid expansion in the irrigation farming as an important cause (Bayat, 2017; Malka, 2018). READ MORE

  4. 4. Training Autoencoders for feature extraction of EEG signals for motor imagery

    University essay from Mälardalens högskola/Akademin för innovation, design och teknik

    Author : Casper Wahl; [2021]
    Keywords : ;

    Abstract : Electroencephalography (EEG) is a common technique used to read brain activity from an individual, and can be used for a wide range of applications, one example is during the rehab process of stroke victims. Loss of motor function is a common side effect of strokes, and the EEG signals can show if sufficient activation of the part of the brain related to the motor function that the patient is training has been achieved. READ MORE

  5. 5. Using Machine Learning for Predictive Maintenance in Modern Ground-Based Radar Systems

    University essay from KTH/Matematisk statistik

    Author : Dina Faraj; [2021]
    Keywords : Predictive Maintenance; Machine learning; Isolation forest; K-means clustering; Logistic regression; Radar systems.; Prediktivt underhåll; Maskininlärning; Isolation forest; K-means klustring; Logistisk regression; Radarsystem.;

    Abstract : Military systems are often part of critical operations where unplanned downtime should be avoided at all costs. Using modern machine learning algorithms it could be possible to predict when, where, and at what time a fault is likely to occur which enables time for ordering replacement parts and scheduling maintenance. READ MORE