Sökning: "Gradient Boosting"

Visar resultat 1 - 5 av 132 uppsatser innehållade orden Gradient Boosting.

1. 1. Sentiment-Driven Cryptocurrency Price Prediction : A Comparative Analysis of AI Models

   Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Jammithri Kotapati; Suma Vendrapu; [2023]
   Nyckelord :Artificial Intelligence; Cryptocurrency Prices; News Articles; Sentiment Analysis; Social Media Posts. ii;

   Sammanfattning : Background: In the last few years, there has been rapid growth in the use of cryptocurrency, as it is a form of digital currency and was developed using blockchain technology, so it is almost impossible to counterfeit cryptocurrency. Due to these features, it has attracted a lot of popularity and attention in the market. LÄS MER

3. 2. Prediction Models for TV Case Resolution Times with Machine Learning

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

   Författare :Borja Javierre I Moyano; [2023]
   Nyckelord :Datasets; Machine Learning ML ; Prediction; Resolution Time RT ; Solve Time; TV Cases; Trouble Tickets TT ; Customer-Related Trouble Tickets Resolution Time; CRM system; BI system; Telecommunications; Dataset; Machine Learning ML ; Prediction; Resolution Time; Solve Time; TV Cases; Trouble Tickets TT ; Kundrelaterade problem Tickets Resolution tid; CRM-system; BI-system; Telekommunikationer.;

   Sammanfattning : TV distribution and stream content delivery of video over the Internet, since is made up of complex networks including Content Delivery Networks (CDNs), cables and end-point user devices, that is very prone to issues appearing in different levels of the network ending up affecting the final customer’s TV services. When a problem affects the customer, and this prevents from having a proper TV delivery service in devices used for stream purposes, the issue is reported through a call, a TV case is opened and the company’s customer handling agents start supervising it to solve the problem as soon as possible. LÄS MER

4. 3. A Predictive Analysis of Customer Churn

   Kandidat-uppsats, KTH/Matematisk statistik

   Författare :Olivia Eskils; Anna Backman; [2023]
   Nyckelord :Churn prediction; CRM; optimization; applied mathematics; machine learning; gradient boosting; random forest; logistic regression; insurance industry; Kundbortfall; CRM; optimering; tillämpad matematik; maskininlärning; gradient boosting; random forest; logistisk regression; försäkringsbranschen;

   Sammanfattning : Churn refers to the discontinuation of a contract; consequently, customer churn occurs when existing customers stop being customers. Predicting customer churn is a challenging task in customer retention, but with the advancements made in the field of artificial intelligence and machine learning, the feasibility to predict customer churn has increased. LÄS MER

5. 4. Winter Wheat Harvest Prediction Using Primarily Satellite Radar Data from Sentinel-1

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Oliver Persson Bogdanovski; Christoffer Svenningsson; [2023]
   Nyckelord :Precision Agriculture; Sentinel-1 SAR; Machine Learning; Winter Wheat; Harvest Prediction; RFI-filtering; Despeckling; Mathematics and Statistics;

   Sammanfattning : Aiding farmers with their tremendous task of sustainably and cost-efficiently feeding the world is of utmost importance. Information technology plays a crucial role in supporting farmers and supplying them with accurate information about their crops. LÄS MER

7. 5. Predicting Breakdowns in Transportation Vehicles using Supervised Learning

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

   Författare :Shuo Li; [2023]
   Nyckelord :Breakdown Prediction; Transportation Vehicles; Diagnose; Gradient Boosting Classifier; Ensemble Model; Förutsägelse av haveri; transportfordon; diagnos; Gradient Boosting Classifier; Ensemblemodell;

   Sammanfattning : Vehicle breakdowns can lead to fatal accidents, increase costs and reduce productivity. Therefore, robust and accurate fault diagnosis and prediction systems are critical to ensure the proper operation of vehicles. Many researchers have used machine learning for the prediction of vehicle breakdowns. LÄS MER