Essays about: "Random Forest Classifier"

Showing result 1 - 5 of 134 essays containing the words Random Forest Classifier.

  1. 1. Land cover classification using machine-learning techniques applied to fused multi-modal satellite imagery and time series data

    University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Author : Anastasia Sarelli; [2024]
    Keywords : Geography; GIS; Land Cover Classification; Landsat; Machine Learning; Earth and Environmental Sciences;

    Abstract : Land cover classification is one of the most studied topics in the field of remote sensing, involving the use of data from satellite sensors to analyze and categorize different land surface types. There are numerous satellite products available, each offering different spatial, spectral, and temporal resolutions. READ MORE

  3. 2. CNN-LSTM architecture for predicting hazardous driving situations

    University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

    Author : Noomi Lindblad; Stefani Platakidou; [2023-10-05]
    Keywords : Data science; Machine learning; LSTM; CNN; Vehicle data; Hazardous driving situation; Deep learning;

    Abstract : This study aims to investigate how a CNN-LSTM model can be used together with recorded vehicle data from trucks and external weather data in order to predict a hazardous driving situation. The dataset consists of three-second-long driving snippets from customer and development trucks registered within Europe. READ MORE

  4. 3. Intrusion Detection in IT Infrastructures using Hidden Markov Models

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Christopher Liu; Sabrina Al-Haddad; [2023]
    Keywords : ;

    Abstract : In the past decades, cloud based services have developed rapidly. And as a result, cybercrimehas increased in sophistication as well as frequency. It therefore becomes vital to have solidprotection against such attacks, especially for infrastructures containing sensitive information. READ MORE

  5. 4. Credit Card Approval Prediction : A comparative analysis between logistic regressionclassifier, random forest classifier, support vectorclassifier with ensemble bagging classifier.

    University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Author : Dhanush Janapareddy; Narendra Chowdary Yenduri; [2023]
    Keywords : Machine Learning; Logistic Regression; Random Forest; Support Vector Machine; Ensemble Learning Bagging.;

    Abstract : Background. Due to an increasing number of credit card defaulters, companies arenow taking greater precautions when approving credit applications. When a customermeets certain requirements, credit card firms typically use their experience todecide whether to grant them a credit card. READ MORE

  6. 5. A requirements engineering approach in the development of an AI-based classification system for road markings in autonomous driving : a case study

    University essay from Blekinge Tekniska Högskola/Institutionen för programvaruteknik

    Author : Srija Sunkara; [2023]
    Keywords : Requirements Engineering; Machine Learning; Goal-Oriented Requirements Engineering; Autonomous Driving; Point Cloud Classification;

    Abstract : Background: Requirements engineering (RE) is the process of identifying, defining, documenting, and validating requirements. However, RE approaches are usually not applied to AI-based systems due to their ambiguity and is still a growing subject. READ MORE