Search Results - (( variable using data algorithm ) OR ( learning application customization algorithm ))
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Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques
Published 2022“…The goal of using a Decision Tree is to create a training model that can use to predict the class or value of the target variable by learning simple decision rules inferred from prior data. …”
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Algorithm comparison for data mining classification: assessing bank customer credit scoring default risk
Published 2024“…The study examines how customer attributes affect virtual experiences. Despite advances in machine learning models for credit assessment, unbalanced datasets and some algorithms’ failure to explain forecasts remain major issues. …”
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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning
Published 2023“…This research explores the application of unsupervised learning, a subset of Artificial Intelligence (AI), to analyze customer behavior in accepting personal loans within the banking sector. …”
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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…Two machine learning model is chosen to build the classification models which are Random Forest (RF) algorithm and Multinomial Naïve Bayes (MNB) algorithm. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…In order to obtain the optimum number of clusters and at the same time could deal with correlated variables in huge data, modified k-means algorithm was proposed. …”
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Stock indicator scanner customization tool using deep reinforcement learning
Published 2022“…Other than that, many current stock indicator scanners only allow user to specify some simple conditions to scan the stocks and do not harness the advancement of machine learning. This project will deliver a web application with dynamic stock prediction model based on deep reinforcement learning or more particularly, Deep Q-Network (DQN) algorithm which enable input customization. …”
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KNN Algorithm to Determine Optimum Agricultural Commodities in Smart Farming
Published 2023“…The algorithm used in this research is KNN, which was chosen because the variable has a numeric data type to perform the matching. …”
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Comparing seabed roughness result from QPS fledermaus software, benthic trrain modeler [BTM] and developed model derived FRM slope variability algorithm for hard coral reef detecti...
Published 2018“…In this study, rugosity is been developed by using QPS Fledermaus software. In ArcGlS software, DEM data will be process by using terrain roughness model that has been derived by using Slope Variability algorithm. …”
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Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The performance of the proposed method is illustrated using simulation study and on glass vessel data with 1920 variables, cardiomyopathy microarray data with 6319 variables, and octane data with 226 dimensions. …”
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SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. …”
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Stock indicator scanner customization tool
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Fault diagnostic algorithm for precut fractionation column
Published 2004“…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing
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Machine learning based route optimization for the travelling salesman problem with pickup and delivery
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Prediction of Machine Failure by Using Machine Learning Algorithm
Published 2019“…Then, the data is cluster by using K Means to produce labeled input that will be trained by using Gradient Boosting Machine, a decision tree algorithm to make prediction. …”
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Final Year Project -
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Predicting Customer Behaviour on Buying Life Insurance using Machine Learning
Published 2026journal::journal article -
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