Sökning: "random Forests"
Visar resultat 1 - 5 av 147 uppsatser innehållade orden random Forests.
1. Land cover classification using machine-learning techniques applied to fused multi-modal satellite imagery and time series data
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : 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. LÄS MER
2. Regression and time estimation in the manufacturing industry
Kandidat-uppsats, Uppsala universitet/Statistik, AI och data scienceSammanfattning : In this thesis an analysis is performed on operation times for different sized products in a manufacturing company. The thesis will introduce and summarise most of the theory needed to perform regression and also cover a worked example where three different regression models are learned, evaluated and analysed. LÄS MER
3. Predicting user churn using temporal information : Early detection of churning users with machine learning using log-level data from a MedTech application
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : User retention is a critical aspect of any business or service. Churn is the continuous loss of active users. A low churn rate enables companies to focus more resources on providing better services in contrast to recruiting new users. LÄS MER
4. Assessing the accuracy of a spatial model of habitat suitability for Calypso bulbosa
Kandidat-uppsats, SLU/Dept. of Biosystems and Technology (from 130101)Sammanfattning : Calypso bulbosa is a rare and visually striking orchid that grows in older mesic to moist forests in the northern half of Sweden. C. bulbosa is red listed as a threatened species (Vulnerable, VU) with a reduction in numbers linked to modern forestry practices and exacerbated by the warming climate. LÄS MER
5. Comparison of Recommendation Systems for Auto-scaling in the Cloud Environment
Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : Background: Cloud computing’s rapid growth has highlighted the need for efficientresource allocation. While cloud platforms offer scalability and cost-effectiveness for a variety of applications, managing resources to match dynamic workloads remains a challenge. LÄS MER