Essays about: "retention prediction"

Showing result 1 - 5 of 28 essays containing the words retention prediction.

1. 1. Utilizing energy-saving techniques to reduce energy and memory consumption when training machine learning models : Sustainable Machine Learning

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

   Author : Khalid El Yaacoub; [2024]
   Keywords : Sustainable AI; Machine learning; Quantization-Aware Training; Model Distillation; Quantized Distillation; Siamese Neural Networks; Continual Learning; Experience Replay; Data Efficient AI; Energy Consumption; Energy-Savings; Sustainable ML; Computation resources; Hållbar maskin inlärning; Hållbar AI; Maskininlärning; Quantization-Aware Training; Model Distillation; Quantized Distillation; siamesiska neurala nätverk; Continual Learning; Experience Replay; Dataeffektiv AI; Energiförbrukning; Energibesparingar; Beräkningsresurser;

   Abstract : Emerging machine learning (ML) techniques are showing great potential in prediction performance. However, research and development is often conducted in an environment with extensive computational resources and blinded by prediction performance. READ MORE

3. 2. Predicting user churn using temporal information : Early detection of churning users with machine learning using log-level data from a MedTech application

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

   Author : Love Marcus; [2023]
   Keywords : User churn; Customer attrition; Artificial neural networks; Log-level analysis; Random forests; Decision trees; Användarbortfall; Kundbortfall; Artificiella neurala nätverk; logganalys; Slumpskogar; Beslutsträd;

   Abstract : 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. READ MORE

4. 3. Customer churn prediction in a slow fashion e-commerce context : An analysis of the effect of static data in customer churn prediction

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

   Author : Luca Colasanti; [2023]
   Keywords : Survival Analysis; Time To Event prediction; Churn retention; Machine Learning; Deep Learning; Customer Clustering; E-commerce; Analisi di sopravvivenza; Previsione del tempo a evento; Ritenzione dall’abbandono dei clienti; Apprendimento automatico; Apprendimento profondo; Segmentazione della clientela; Commercio elettronico; Överlevnadsanalys; Tid till händelseförutsägelse; Churn Prediction; Maskininlärning; Djuplärning; Kundkluster; E-handel;

   Abstract : Survival analysis is a subfield of statistics where the goal is to analyse and model the data where the outcome is the time until the occurrence of an event of interest. Because of the intrinsic temporal nature of the analysis, the employment of more recently developed sequential models (Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM)) has been paired with the use of dynamic temporal features, in contrast with the past reliance on static ones. READ MORE

5. 4. A Predictive Analysis of Customer Churn

   University essay from KTH/Matematisk statistik

   Author : Olivia Eskils; Anna Backman; [2023]
   Keywords : 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;

   Abstract : 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. READ MORE

6. 5. CUSTOMER CHURN PREDICTION MODEL IN TELECOMMUNICATION SECTOR USING MACHINELEARNING TECHNIQUE

   University essay from Uppsala universitet/Statistiska institutionen

   Author : Nayema Taskin; [2023]
   Keywords : Telecommunication; Customer Retention; Churn Prediction; Machine Learning.;

   Abstract : Customer churn is a critical problem faced by telecom companies, leading to lost revenue and increased marketing costs. In the highly competitive telecommunication sector, customer retention is essential for success. It costs five to seven times more toacquire a new customer than it does to retain an existing one. READ MORE