Search Results - data distribution ((mining algorithm) OR (means algorithm))
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. …”
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A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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Fuzzy Soft Set Clustering for Categorical Data
Published 2024“…Conventional clustering, such as k-means, cannot be openly used to categorical data. …”
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Hybrid Neural Network With K-Means For Forecasting Response Candidate In Direct Marketing
Published 2014“…K-means algorithm grouping process by minimizing the distance between the data and designed can handle very large dataset also continuous and categorical variable for handling imbalanced dataset. …”
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Satisfiable Integer Programming Algorithm On Distributed Inter Process Communication (SIP-DIPC)
Published 2019“…Data Analytics is a superset to Data Mining. Data mining algorithm is getting popular support in recent development of Big Data. …”
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Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation
Published 2020“…There are several data mining tasks such as classification, clustering, prediction, summarization and others. …”
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Discovery of SIP/DRIP approach in distributed inter process communication
Published 2023“…Classification modeling in data mining has evolved since 1990's. Many methods have been introduced and experimented. …”
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Analysis using data mining techniques: the exploration and review data of diabetes patients / Syarifah Adilah Mohamed Yusoff ... [et al.]
Published 2025“…In this statistical summary procedure, the distribution of attributes and their interactions are crucial for accurately processing the data in accordance with the selected classification or data mining techniques to be performed. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. …”
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Final Year Project / Dissertation / Thesis -
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Building classification models from imbalanced fraud detection data / Terence Yong Koon Beh, Swee Chuan Tan and Hwee Theng Yeo
Published 2014“…Building classification models from such imbalanced data sets is a relatively new challenge in the machine learning and data mining community because many traditional classification algorithms assume similar proportions of majority and minority classes. …”
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Binary vote assignment on grid quorum replication technique with association rule
Published 2018“…Performance of the BVAGQ-AR technique comprised the following steps. First step is mining the data by using Apriori algorithm from Association Rules. …”
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A novel approach to data mining using simplified swarm optimization
Published 2011“…Data mining has become an increasingly important approach to deal with the rapid growth of data collected and stored in databases. …”
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis
Published 2016“…A semiconductor manufacturing case study with Work In Progress data and true alarm data is used to proof the proposed algorithm. …”
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