Search Results - (( parametric classification learning algorithm ) OR ( java data prediction algorithm ))
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Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach
Published 2023“…This study investigates the application of Decision Trees (DTs), a non-parametric supervised learning method, renowned for its simplicity, interpretability, and wide applicability in various domains, including machine learning for classification and regression tasks. …”
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Article -
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Mapreduce algorithm for weather dataset
Published 2017“…In addition, these characteristics also contribute to the complexity on the data processing and prediction. Big Data analytics is a new concept to process the Big Data. …”
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Thesis -
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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MapReduce algorithm for weather dataset
Published 2018“…In addition, these characteristics also contribute to the complexity on the data processing and prediction. Big Data analytics is a new concept to process the Big Data. …”
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Research Report -
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Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques
Published 2022“…This study aims to predict the ratings of Google Play Store apps using decision trees for classification in machine learning algorithms. 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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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This prediction can be made by cluster the new data with the old data and observe where the data belongs. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms
Published 2018“…The experimental results are also thoroughly evaluated and verified via non-parametric statistical analysis. Based on the obtained experimental results, the OGC, DPSO, and VDEO frameworks achieved an average enhancement up to 24.36%, 9.38%, and 11.98% of classification accuracy, respectively. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…Besides, an android application is being cre-ated to give therapy based on machine learning predictions. To collect data, we enlisted the help of 4,500 people. …”
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Image Splicing Detection With Constrained Convolutional Neural Network
Published 2019“…The constrained layer enables the CNN model to learn the required features directly from ubiquitous image input and then performs classification. …”
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Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms
Published 2020“…In this study, 30 m Landsat 8 data were processed using a cloud computing platform of Google Earth Engine (GEE) in order to classify oil palm land cover using non-parametric machine learning algorithms such as Support Vector Machine (SVM), Classification and Regression Tree (CART) and Random Forest (RF) for the first time over Peninsular Malaysia. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…Thus, there is a need to automate the process of identifying and predicting (positive, negative, or neutral class) these cyber-trooping data. …”
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Thesis -
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…Besides, an android application is being cre-ated to give therapy based on machine learning predictions. To collect data, we enlisted the help of 4,500 people. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…New Iterative Alternating Group Explicit (NAGE) is a powerful parallel numerical algorithm for multidimensional temperature prediction. …”
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Conference or Workshop Item -
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024“…The second-level learner uses logistic regression (LR) to aggregate the final prediction output. The landslide data together with its conditioning factors (feature variables) collected from three districts in the Central Java Province, Indonesia, has been used as the case study for the LSM. …”
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The feed forward and radial basis functions networks show higher learning capabilities than support vector machines and rough set classifier in the classification of datasets comprising more than two classes. …”
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Monograph -
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…Two sets of experimental data involving 20 diabetic patients and 20 healthy subjects were collected from CITO laboratory Semarang Central Java, Indonesia. …”
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Thesis -
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Computational analysis of biological data: Where are we?
Published 2024“…Computer modeling allows such electrical stimulations using statistics, bioinformatics and advanced machine-learning algorithms. The current book chapter discusses the advantages of computational modeling in studying biomedical research. …”
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Book Chapter
