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Keyword: TreeComparative Study of J48 Decision Tree and CART Algorithm for Liver Cancer Symptom Analysis Using Data from Carnegie Mellon University
Liver cancer is a major contributor to cancer-related mortality both in the United States and worldwide. A range of liver diseases, such as chronic liver disease, liver cirrhosis, hepatitis, and liver cancer, play a role in this statistic. Hepatitis, in particular, is the main culprit behind liver cancer. As a consequence, it is decisive to…
Read MoreTree-Based Ensemble Models, Algorithms and Performance Measures for Classification
An ensemble method is a Machine Learning (ML) algorithm that aggregates the predictions of multiple estimators or models. The purpose of an ensemble module is to provide better predictive performance than any single contributing model. This can be achieved by producing a predictive model with reduced variance using bagging, and bias using boosting. The Tree-Based…
Read MoreDevelopment and Analysis of Models for Detection of Olive Trees
In this paper, an automatic method for detection of olive trees in RGB images acquired by an unmanned aerial vehicle (UAV) is developed. Presented approach is based on the implementation of RetinaNet model and DeepForest Phyton package. Due to fact that original (pretrained) model used in DeepForest package has been built on images of various…
Read MoreAssessment of Electromagnetic-Based Sensing Modalities for Red Palm Weevil Detection in Palm Trees
In this paper, we investigate the utilization of three effective detection methods to identify potential threats of insects in date palm trees. The detection techniques presented here are the application of infrared radiation, microwave antennas and metamaterials based sensors. Experimental trials using IR radiation took place in a local farm. Moreover, the second sensing system…
Read MoreEnhancing Decision Trees for Data Stream Mining
Data stream gained obvious attention by research for years. Mining this type of data generates special challenges because of their unusual nature. Data streams flows are continuous, infinite and with unbounded size. Because of its accuracy, decision tree is one of the most common methods in classifying data streams. The aim of classification is to…
Read MoreDetection and Counting of Fruit Trees from RGB UAV Images by Convolutional Neural Networks Approach
The use of Unmanned Aerial Vehicle (UAV) can contribute to find solutions and add value to several agricultural problems, favoring thus productivity, better quality control processes and flexible farm management. In addition, the strategies that allow the acquisition and analysis of data from agricultural environments can help optimize current practices such as crop counting. The…
Read MoreImproved Design and Recommendations for Street Lighting in Gitega City
The article discusses the possibility of using solar energy for street lighting systems in the city of Gitega, in the Republic of Burundi. Analysis of weather and climate conditions of the city was carried out and an effective street lighting system based on solar mini-power plants using an intelligent control system developed. Calculations of technical…
Read MoreDependency Head Annotation for Myanmar Dependency Treebank
Complete manual annotation of dependency treebank needs resources like annotators and annotation tools and takes long time and has high possibility of inconsistent annotations for free word order languages such as Myanmar. This paper describes a dependency head annotation scheme with Universal part-of-speech and Universal Dependencies for Myanmar dependency treebank. Currently 22,810 sentences and 680,218…
Read MoreIntrusion Detection and Classification using Decision Tree Based Key Feature Selection Classifiers
Feature selection method applied on an intrusion dataset is used to classify the intrusion data as normal or intrusive. We have made an attempt to detect and classify the intrusion data using rank-based feature selection classifiers. A set of redundant features having null rank value are eliminated then the performance evaluation using various feature selection…
Read MoreMalware Classification Using XGboost-Gradient Boosted Decision Tree
In this industry 4.0 and digital era, we are more dependent on the use of communication and various transaction such as financial, exchange of information by various means. These transaction needs to be secure. Differentiation between the use of benign and malware is one way to make these transactions secure. We propose in this work…
Read MoreFPGA Acceleration of Tree-based Learning Algorithms
Machine learning classifiers provide many promising solutions for data classification in different disciplines. However, data classification at run time is still a very challenging task for real-time applications. Acceleration of machine-learning hardware solutions is needed to meet the requirements of real-time applications. This paper proposes a new implementation of a machine learning classifier on Field…
Read MoreNearest Neighbour Search in k-dSLst Tree
In the last few years of research and innovations, lots of spatial data in the form of points, lines, polygons and circles have been made available. Traditional indexing methods are not perfect to store spatial data. To search for nearest neighbour is one of the challenges in different fields like spatiotemporal data mining, computer vision,…
Read MoreUniversity Students Result Analysis and Prediction System by Decision Tree Algorithm
The main assets of universities are students. The performance of students plays a vital role in producing excellent graduate students who will be the future viable leader and manpower in charge of a country’s financial and societal progress. The purpose of this research is to develop a “University Students Result Analysis and Prediction System” that…
Read MoreZebrafish Larvae Classification based on Decision Tree Model: A Comparative Analysis
Screening the abnormal development of the zebrafish embryos before and after being hatched for a large number of samples is always carried out manually. The manual process is presented as a tedious work and low-throughput. The single female fish produce hundreds of eggs in every single mating process, the samples of the zebrafish embryos should…
Read MoreApplication of Modularization Idea of Fault Tree in Ship Pilotage Risk Decision Making
Ship pilotage risk decision-making problems, which is an important issue affecting the safety of navigation. Before the study on the risk decision of ship pilotage, all use direct analysis of fault tree methods. In this paper, through the process analysis of ship pilotage fault tree, the model of fault tree is standardized and simplified. The…
Read MorePredictive Analytics in Marketing: Evaluating its Effectiveness in Driving Customer Engagement
Understanding and responding to customer feedback is critical for business success. Customer response data offers valuable insights into preferences, behaviours, and sentiment. By analysing this data, businesses can optimize strategies, enhance customer experiences, and drive growth. Many analysis have been conducted in this field, while the review covers a broad range of AI and ML…
Read MoreOn Mining Most Popular Packages
In this paper, we will discuss two algorithms to solve the so-called package design problem, by which a set of queries (referred to as a query log) is represented by a collection of bit strings with each indicating the favourite activities or items of customers. For such a query log, we are required to design…
Read MoreEEG Feature Extraction based on Fast Fourier Transform and Wavelet Analysis for Classification of Mental Stress Levels using Machine Learning
Mental stress assessment remains riddled with biases caused by subjective reports and individual differences across societal backgrounds. To objectively determine the presence or absence of mental stress, there is a need to move away from the traditional subjective methods of self-report questionnaires and interviews. Previously, it has been evidence that EEG Oscillations can discriminate mental…
Read MoreThe First Application of the Multistage One-Shot Decision-Making Approach to Reevaluate a Technology Project Decision Problem
Decision-makers must make a suitable sequence of decisions under uncertainty in a relatively long period for particular projects and situations. Conventional decision-making approaches under uncertainty are based on expected utility theory and do not sufficiently reflect the one-time nature of decisions. Similarly, the conventional approaches do not adequately incorporate the decision-maker’s intuitions in the decision-analysis…
Read MoreAnalysis of Different Supervised Machine Learning Methods for Accelerometer-Based Alcohol Consumption Detection from Physical Activity
This paper builds on the realization that since mobile devices have become a common tool for researchers to collect, process, and analyze large quantities of data, we are now entering a generation where the creation of solutions to difficult real-world problems will mostly come in the form of mobile device apps. One such relevant real-life…
Read MoreARAIG and Minecraft: A Modified Simulation Tool
Various interruptions to the daily lives of researchers have necessitated the usage of simulations in projects which may not have initially relied on anything other than physical inquiry and experiments. The programs and algorithms introduced in this paper, which is an extended version of research initially published in ARAIG And Minecraft: A COVID-19 Workaround, create…
Read MoreA Supervised Building Detection Based on Shadow using Segmentation and Texture in High-Resolution Images
Building detection in aerial or satellite imagery is one of the most challenging tasks due to the variety of shapes, sizes, colors, and textures of man-made objects. To this end, in this paper, we propose a novel approach to extracting buildings in high-resolution images based on prior knowledge of the shadow position. Firstly, the image…
Read MoreGeneralized Linear Model for Predicting the Credit Card Default Payment Risk
Predicting the credit card default is important to the bank and other lenders. The credit default risk directly affects the interest charged to the borrower and the business decision of the lenders. However, very little research about this problem used the Generalized Linear Model (GLM). In this paper, we apply the GLM to predict the…
Read MoreInnovations in Recruitment—Social Media
The main objective and contribution of the paper is to describe the creation of a model to support recruitment using social media information and its deployment in practice. The model includes the design of an automated solution for downloading social media data and a proposal for the subsequent analysis and creation of a predictive model…
Read MorePredicting School Children Academic Performance Using Machine Learning Techniques
The study aims to assess the machine learning techniques in predicting students’ associated factors that affect their academic performance. The study sample consisted of 5084 middle and high school students between the ages of 10 and 17, attending public and UNRWA schools in the West Bank. The ‘Health Behaviors School Children’ questionnaire for the 2013-2014…
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