IEEE

Evaluating the Performance of Clinical data using Machine learning Approach– An Ensemble Model

Abstract: In the rapidly evolving field of healthcare, accurate clinical predictions are paramount for effective disease management and treatment planning. This paper introduces a novel ensemble ...
IEEE

Enhancing Customer Retention: A Federated Machine Learning Framework for Banking Churn Prediction

Abstract: Customer attrition has become the significant challenge for the bank, making large volume of customers to migrate to other banks, as the banks keeps providing multiple benefits to the ...
IEEE

Forest Fire Forecasting Leveraging Modis Satellite Fire Data Using Machine Learning For Jharkhand State, India

Abstract: Forest fires pose significant environmental and economic threats, necessitating robust predictive models for better management and prevention. This study focuses on the temporal and spatial ...
IEEE

Harnessing Machine Learning for Effective Customer Segmentation

Abstract: The paper’s objective is to utilize machine learning techniques for customer segmentation. We aim to identify significant patterns and segments within a customer base to enhance marketing ...
IEEE

Optimizing Customer Satisfaction Through Sentiment Analysis: A BERT-Based Machine Learning Approach to Extract Insights

Abstract: In the era of digital transformation, customer feedback has become crucial for improving service quality. This study aims to enhance customer satisfaction through sentiment analysis ...
IEEE

Customer Segmentation using Mini Batch K-Means Clustering Algorithm

Abstract: Today, especially in this era of data, everything is becoming more mechanized. Data is the new electricity of the globe. This knowledge may help a lot of businesses in their marketing ...
IEEE

Machine Learning Insights for Predicting Customer Behavior in Online Retail

Abstract: The research work reports a comprehensive analysis of predictive analytics of customer behavior on e-commerce based on high-end data science and artificial intelligence techniques. The ...
IEEE

3D Semantic Segmentation of Airborne & UAV LiDAR Point Clouds for Precise Tree Counting: a Machine Learning Approach

Abstract: In a world where sustainable forest management and understanding of our ecosystems have become priorities, accurately and efficiently counting trees, especially in geographically challenging ...
IEEE

Market Segmentation Using Machine Learning and Data Analysis: A Comprehensive Study

Abstract: This research explores the integration of machine learning into market segmentation, a strategy traditionally reliant on demographic, geographical, and psychographic traits. With the rise of ...
IEEE

Anomaly Detection in Sensor Data using Machine Learning

Abstract: Our research investigates the application of single-class Support Vector Machine (SVM) for anomaly detection, which is critical for predictive maintenance. The study utilizes real-world ...
IEEE

Customer Churn Prediction Analysis for Retention Using Ensemble Learning

Abstract: In the 21st century, there is a handful of information on the Internet. It is easy for customers to switch to a competing company in any sector. It is important for a company to retain its ...
IEEE

Deep Learning-Based Railway Foreign Object Intrusion Intelligent Perception Using Attention-Aggregated Semantic Segmentation

Abstract: Foreign object intrusion detection (FOID) is one of the critical tasks to ensure the safe and efficient operation of trains. Semantic segmentation, which involves pixel-level recognition of ...