data mining IEEE PAPER 2022


Data mining is the process of understanding data through cleaning raw data, finding patterns, creating models, and testing those models. It includes statistics, machine learning, and database systems. Data mining is the process of finding anomalies, patterns and correlations within large data sets to predict outcomes. Using a broad range of techniques, you can use this information to increase revenues, cut costs, improve customer relationships, reduce risks







Data Mining Methods: A Review
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of Big Data Mining techniqueswith the most common data mining algorithms suitable to be and in general acts as a guideline to data mining researchers to have an outlook on what

Retrospectively evidencing research impact using online data mining
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data mining tools. The aim of this paper is to demonstrate several ways in which online data mining In the next section, we outline the various online data sources that we will consider,

IMPLEMENTING SALES DECISION SUPPORT SYSTEM USING DATA MART BASED ON OLAP, KPI, AND DATA MINING APPROACHES
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data from a data warehouse. Third, building sales cube and knowledge-driven sales is supported on the basis of three data mining DSS used data mart on the basis of online analytical

DATAMINING AND ITS APPLICATIONS
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from a larger set of data . Data mining involves effective data collection and warehousing The major steps involved in a data mining process are extracted, transform and load data

The Use of Data Mining and Automated Social Networking Tools in Virtual Learning Environments to Improve Student Engagement in Higher Education
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data that has the potential to inform and improve this pedagogy. The question this paper explores is how might the development of data mining and that educational data mining has the The utilization of data mining and machine learning are often produced using data processing and machine learning the assistance of association rule mining and genetic algorithms.

COVID-19 DISEASE RECOGNITION USING DISTRIBUTED DATA MINING AND DEEP LEARNING
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data mining is a growing topic in data mining that allows to perform parallel and distributed data mining the classification task, we explain the distributed data mining through this task.

Using Data Mining to Prediction Fashion Sales
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purchase data . Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining A data mining approach to the prediction of corporate failure.scholars have approached data mining and the more recent developments in data mining in Data mining applications and strategies are being used by businesses to produce market

On Multi-modal Data Mining and Advanced Machine Learning Research
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on streaming data . Due to this situation, this project explores data characteristics in Big Data on streaming data and perform query optimization for massive data stream applications.

Role and Relevance of Statistics in Data Mining Business Environment
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Starting from the fact that statistics traditionally deals with data analysis, data in a new, data mining environment, whose key definition is computer-aided work with large amounts of data

Development and Upgrading Plan for FMCG Industry Based on Data Mining
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discuss how to establish a data warehouse based on traditional data mining objects, the preparation of data mining model and big data analysis, and the application of new data mining

Importance of data mining to generate knowledge in organizations
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Esta tarea implica generalmente preprocesar los datos, hacer minería de datos ( data mining Qu es el Data Mining o la minería de datos y qu ventajas nos aporta . 2021. Consultado

Data mining technology for the identification and threshold of governing factors of landslide in the Three Gorges Reservoir Area
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Compared with the traditional data analysis process, 73 data mining has attracted great attention for its ability in exploring the inherent correlation criteria of data 74 (Ma et al.

USING DATA MINING TOOLS TO PREDICTION OF GOING CONCERN ON AUDITOR OPINION-EMPIRICAL STUDY IN IRAQI COMMERCIAL
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and from here became the need to use data mining techniques more widely. The difficult task of data that the company deals with, the importance of using data mining techniques in of Twitter data for predicting public health. Here, various methods were used for mining the Twitter data for public health monitoring. Research papers where Twitter data is classified as

A DIFFERENT APPROACH TO THE MONITORING OF THE QUALITY OF DRINKING WATER WITH DATA MINING TOOLS
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(FA) which taFe place within data mining tools. The relationship It has been discussed how the data set analysis reY sults the data mining methods envisaged in the study from the data

Study of Various Data Mining Methods to Select the Appropriate Method for Managers to Make Decisions in Urban Management
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to analyze the data of the Tehran Municipality websites and provide data mining solutions for The data collection method was the field. The statistical population was selected from 220

Data Mining Techniques to Predict Default in LendingClub
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This study aims to build a predictive model for default in LendingClub using Artificial Neural Networks, and to compare its performance to the Logistic Regression model. The datasetA Novel Influence Maximization Algorithm for a Competitive Environment Based on Social Media Data Analytics Jie Tong, Leilei Shi, Lu Liu, John Panneerselvam, and Zixuan

ANALYSIS OF PROBLEMS AND CHALLENGES OF EVOLUTIONARY ALGORITHMS IN DATA MINING
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The major aim of this work deals with the study about evolutionary algorithms and their applications in real-world scenario. Several categories of evolutionary algorithms such as genetic

Multiscale Data Analytics for Residential Active Power Measurements through Time Series Data Mining
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data which can be used to build data driven prediction and classification models. Directly using these large and unprocessed data purpose time series data mining technique which is

Statistical models and algorithms for data mining and machine learning
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A review of the literature about data mining applied to sport in general, and to basketball in particular, with a deep analysis concerning the outcome prediction literature. The problem of

Analysis of Students Critical Thinking Skills Using Data Mining Approaches (Survey Based Research)
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We can also analyse which data mining algorithm gives us the highest accuracy based on our data and, address some of the open problems we encounter as we go along, based

Data Mining of Patents: A Study on Application of Machine Learning in Animal Husbandry
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concepts to extract patterns or knowledge from huge set of data . The concepts of data mining are still In the present study, patent data is used for data mining to bring out development of

Research on Development Path of Culinary Specialty in Secondary Vocational Schools Based on Data Mining Technology COVID-19 Epidemic Background
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Data mining is a cross-discipline formed data mining can be any type of data source. It can be a relational database, such a data source containing structured data ; it can also be a data

Risk factors and Interaction analysis of Hypertension in People who were Overweight and obesity: Based on Machine Learning and Data Mining
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Objective To screen the independent risk factors of hypertension in People who were Overweight and obesity by Logistic regression and Decision tree model, and to analyze the two

A DATA MINING APPROACH TO STUDY THE MENTAL HEALTH OF INDIAN STUDENTS DURING COVID-19 PANDEMIC
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Data mining is an approach for analysing huge observational datasets data mining is to identify unknown patterns in datasets and to present the information in novel ways. Data mining

A Hybrid Approach to Detect Injection Attacks on Server-side Applications using Data Mining Techniques
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in unauthorized access to sensitive data such as passwords, vulnerabilities, various data mining and machine learning the method based on data mining is conducive to high-

Methods for efficient utilization of SOM in data mining
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data exploration process based on the SOM, see Figure 15.1. The work has been motivated by a number of practical data mining projects where SOM has been a central data the data

Landscape of TP53 Alterations in Chronic Lymphocytic Leukemia via Data Mining Mutation Databases.
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Locus-specific databases are invaluable tools for both basic and clinical research. The extensive information they contain is gathered from the literature and manually curated by experts

Age-and sex-specific pediatric LMS-Percentiles for Laboratory Parameters enabled by Data mining
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Background: Various laboratory parameters routinely measured in pediatric practice covariate with sex and age. Conventional reference intervals are not suitable to account for this

Modeling of Reference Crop Evapotranspiration in Wet and Dry Climates Using Data Mining Methods and Empirical Equations
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considered, and MARS is a better data mining method by considering accuracy, uncertainty, a comprehensive investigation of data mining ability in ETo modeling, all data in humid and

of Forkhead Box M1 in Esophageal Squamous Cell Carcinoma Tissues: A Study Based on In-house Immunohistochemistry, RNA-sequencing, and Data Mining
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Finally, mRNA-sequencing data of about 000 genes was obtained. In order to make more researchers bene t from our data we also uploaded the mRNA-sequencing data to gene

Student Performance Prediction Using Case Based Reasoning Knowledge Base System (CBR-KBS) Based Data Mining
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finding a vast number of data patterns and information. Data mining was known for the use By data processing the data mining process is about describing the past and forecasting the

Evaluating the Efficiency of Sugarcane Harvesting Units Using a Combined Approach to Data Envelopment Analysis and Data Mining
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in data volume and the need to analyze information and predict variables, data mining especially the decision tree, can be helpful. The decision tree is one of the data mining methods.

Biotic and Abiotic Sources of Stress on Wild Rocket Classified by Leaf-Image Hyperspectral Data Mining with an Artificial Intelligence Model
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Background: Wild rocket (Diplotaxis tenuifolia) is prone to soil-borne stresses under intensive cultivation systems devoted to ready-to-eat salad chain, increasing needs for external

Co-clustering Numerical Data under User-defined Constraints STATISTICAL ANALYSIS AND DATA MINING (2010) 3
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First, these articles concern only 0/1 data mining . More importantly, we propose here to work directly on the data ie, without any postprocessing of collections of local patterns that have

Whos your data Primary immune deficiency differential diagnosis prediction via machine learning and data mining of the USIDNET registry
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on data mining data mining study, we aimed to predict PID diagnoses with a supervised machine learning algorithm based on classi cation tree boosting. METHODS: Through a data

MINING OF NUTRITIONAL INGREDIENTS IN FOOD FOR DISEASE ANALYSIS
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In addition, the data in this research is continuous and does not contain any choice data mining that is relevant to the subject. There is a thorough description of the specific data mining

PANDORA: Continuous mining software repository and dataset generation
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tools to support mining software repositories studies. This section reports and discusses some of the most used and best-known tools supporting data mining and data analysis, along

Pattern Mining : Current Challenges and Opportunities
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Pattern mining is a key subfield of data mining that aims at developing algorithms to discover interesting patterns in databases. The discovered patterns can be used to help

HEART DISEASE PREDICTION USING NEURAL NETWORKS BASED ON MINING APPROACH
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In this research paper, we have presented Heart disease prediction system (HDPS) using data mining and artificial neural network (ANN) perceptron neural network along with back

USING TEXT MINING TO ANALYSE WEB ADDRESSES (URLS)
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There has also been an increase in data mining . Data mining is the process of finding patterns, correlations and anomalies within large data sets to predict outcomes. The most natural

Image Mining Using Smart Multi-Agent System
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data mining can be extended for mining from structured data that can influence the data mining process, and data mining can This interaction and integration of Agent and Data mining

Sentiment Evolution Analysis and Association Rule Mining for COVID-19 Tweets
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This article presents a data mining study carried out on social media users in the context of COVID-19 and offers four main contributions. The first one consists in the construction of a

Sport action mining : Dribbling recognition in soccer
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This research aims to fill existing gaps in the literature by proposing a novel framework that combines data mining and machine learning approaches to automatically detect dribbling

Incorporating student opinion into opinion mining
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We generated Data Set 1 with the EM algorithm which selected the ground truth label for each text message based on the example text and labels provided by Cohort 1 Students. Werule mining is one of the most common data mining This paper studies the mining rules from two representations of core processor architecture for mining non-redundant sequential

Seq2Pat: Sequence-to-Pattern Generation for Constraint-based Sequential Pattern Mining
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Our tool is readily available for any mining application that deals with data encoded as sequences of symbols. For continuous sequences, such as time series, discretization can be

Inference Control in a Diabetes Data Set Algorithm
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data mining is a research field designed to resolve confidentiality issues arising from data mining . The inference problem in databases occurs when sensitive information can be

Mining limited data for more robust and generalized ML models
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J Yu, H Chang, K Lu12 2022 alisec-competition.oss-cn-shanghai to-end model-driven data mining method is proposed to mine the best data and train the representative data among all possible data for training. Obviously, mining valuable data manu

Ridge Regression based Missing Data Estimation with Dimensionality Reduction: Microarray Gene Expression Data
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evolved vast data is useful for extracting the knowledge, making analysis and visualization for decision. Data mining is a technique used for generating useful information from the data .Abstract: Data has indisputably proven overtime to have a better idea and with the surge of big data in the era of coronavirus, research initiatives in the field of data mining continues to

Automating ETL and Mining of Ethereum Blockchain Network
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Blockchain introduces new directions in online financial data mining and analysis. ) as graphs to provide new insights through network mining . Graph-based analyses are powerful tools

Discussion on the Construction and Application of Performance Appraisal in Human Resource Management under the Background of Big Data
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On the basis of the original theory, it creatively uses the data mining technology in big data technology to construct the framework of performance appraisal, and then designs theDue to its versatility, FIM is viewed as a general and popular data mining Mining (HUIM) provides for a model where the aforementioned factors can be accommodated during mining .

DATA SCIENCE AND AUTOMATION
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Data is the new oil and data science is «sexy» What data mining task we want to solve Put the model (or the data mining steps) into production

Analyzing Land Use Change and Climate Data to Forecast Energy Demand for a Smart Environment
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We assess changes in energy demand by comparing results from the data mining / machine learning techniques of Support Vector Machines (SVM) and Artificial Neural Network (ANN).

data mining IEEE PAPER 2021




Spatial Data Mining Methods Databases and Statistics Point of Views
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This article reviews the approaches used in data mining to perform a geographical study of regional datasets coupled with Geographic Information Systems (GIS). Firstly, we can look at the functions of data mining used by such data and then illustrate their precision compared With the rapid development and popularization of Internet and mobile communication technologies, text data mining has attracted much attention. In particular, with the wide use of new technologies such as cloud computing, big data, and deep learning, text mining has Educational data mining is used to discover significant phenomena and resolve educational issues occurring in the context of teaching and learning. This study provides a systematic literature review of educational data mining in mathematics and science education. A total ofGainful livestock farming requires selective breeding of animals with certain heritable desirable traits which gives profitability in terms of farm produce. Modern dairy animals are selected for traits which directly or indirectly contribute to high milk production. The concept

A Similarity based K-Means Clustering Technique for Categorical Data in Data Mining Application
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Clustering plays a major role in the data mining application, because it divides and groups the data effectively. In the pattern analysis, two major challenges occur in real-life applications that includes handling the categorical data and the availability of correctly

Text documents clustering using data mining techniques.
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Increasing progress in numerous research fields and information technologies, led to an increase in the publication of research papers. Therefore, researchers take a lot of time to find interesting research papers that are close to their field of specialization. Consequently

Scalable Analysis of COVID-19 Spatiotemporal Patterns Based on Data Mining Tools: Using 3D Bins to Predict Short-time Focus Locations
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Background: An interesting research line is related to COVID-19 behavior from a territorial and temporal perspective. Hence, the use of 3D space-time bins is a useful tool to contrast limitations of visual assessment and reveal the detailed areas most at risk for the pandemic

Data mining approach to analyzing intrusion detection of wireless sensor network
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Wireless sensor network (WSN) is a collection of wireless sensor nodes which are distributed in nature and a base station where the dispersed nodes are used to monitor and the physical conditions of the environment is recorded and then these data are organized

The relationship between the coat colors of Kars Shepherd Dog and its morphological characteristics using some data mining methods
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The aim of the study was to apply various data mining techniques to determine coat colour and live weight of Kars shepherd dog. C5. 0, MARS (Multivariate Adaptive Regression Splines) and Bagging MARS (Bootstrap Aggregating Multivariate Adaptive Regression

Predicting the Behavior of Blood Donors in National Blood Bank of Ethiopia Using Data Mining Techniques.
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A modern technology used for extracting knowledge from a huge amount of data using different models and tasks such as prediction and description is called data mining . The data mining approach has a great contribution on solving a different problem for data miners. This

An Enhanced Network Intrusion Detection System Using Data Mining
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This research work treats the enhanced network intrusion detection system via the utilization of data mining techniques to detect attacks cause by intruder in a network for attackers. Many research works have done in area of intrusion detection in a network we will be

Application of data mining in identifying and discovering hidden patterns of theft
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Crime prevention has always been one of the basic and important issues in human life that have been applied in various ways throughout history. Due to the development of information and communication technologies and the launch of comprehensive information

Application Analysis of Data Mining Technology in the Field of Learning Analysis in China From the Perspective of Content Analysis
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Learning analysis has gradually become the focus of attention of the majority of educators, and data mining has brought more possibilities for learning analysis. This study takes CNKI literature as the research object, searches data mining and learning analysis as

The Basic Research of Data Mining Of Input With Weighted matrix On Data Classification Based on Neural Network
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How to choose the feature for training the back-propagation neural network is a well-known problem. The basic principles are to avoid encrypting the datas underlying structure and avoid using irrelevant inputs. So people propose to use the data mining technology on the

Diverse Analysis of Data Mining and Machine Learning Algorithms to Secure Computer Network
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Abstract Information and Communication Technologies, to a long extent, have a major influence on our social life, economy as well as on worldwide security. Holistically, computer networks embrace the Information Technology. Although the world is never free from people

Test Performance Prediction Using Data Mining
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Educational Data Mining (EDM) is an emerging interdisciplinary research field which involves exploring large scale datasets that come from educational settings in order to better understand students and the settings in which they learn. This is done with the aim of being Data mining plays the key role in crime analysis. There are various number of different algorithm in previous research papers like virtual identifier, pruning strategy, support vector machines and apriori algorithms. VID (Virtual ID) is to find relationship between record

AN ANALYSIS OF APPLICATIONS OF DATA MINING IN WEATHER FORECASTING
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Climate change is becoming a serious impact nowadays on the environment. Climate change refers to extreme changes in weather conditions. It leads to major threat for human beings. The drastic changes in weather, makes people difficult in predicting the climaticThe Intrusion Detection System (IDS) plays a significant part in security schemes. Network IDS (NIDS) seems to have a position in the detection of harmful and unauthorized networks and systems among its various forms. The identification of Denial of Service (DoS) and

Development and Implementation of Locally-Executed Data Mining on Smartphones
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Abstract Development and Implementation of Locally-Executed Data Mining on Mobile Devices by Darren Yates. Data mining is the science of extracting information orknowledgefrom data. It is a task commonly executed on cloud computing resources, as

DATA MINING OF ONLINE QUIZ LOG FILES: CREATION OF AUTOMATED TOOLS FOR IDENTIFICATION OF POSSIBLE ACADEMIC MISCONDUCT IN LARGE
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The rapid shift to remote course delivery in March during the COVID-19 pandemic presented a significant challenge for administering fair and reliable student assessments. Students and instructors who were not specifically trained for an online learning

Development of Predictive Model for Infant Media Addiction Through Text Mining and Data Mining
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The purpose of this study is to examine major variables of predicting childs media addiction through analyzing the text mining and the data mining . For this, the key-word analysis, the topic modeling analysis and the sentiment analysis were carried out after collecting

Mathematical modelling of evapotranspiration by using remote sensing and data mining
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Precise evaluation of evapotranspiration in an extended area is crucial for water requirement. By 26 using remote sensing evapotranspiration algorithms, many climatological variables are needed. 27 In case of using climatological variable

STUDENT PERFORMANCE PREDICTION USING EDUCATIONAL DATA MINING
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Prediction of students performance has always been significant for enhance learning. Student Performance Prediction is the prominent application of Educational Data Mining (EDM). EDM has developed as one of the emerging research field in recent years. ThisThe Universe is a synonym of a lot of creations and activities. It is a dynamic world. Everything is changing in respect of others. The existence of life at heavenly bodies is one of the most important creations of the nature. It caused the genesis of numerous species across

WAY TO SMART LIFE USING DATA MINING
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Information offers numerous prerequisites to the end clients, for example, programming, association and stage go on. In this proposed framework, we concentrate about carefully mining the information on social media. Online media turns out to be well known from the

EFFECTIVE PREDICTION OF PATIENT ADMISSION IN HOSPITAL USING DATA MINING CLASSIFICATION ANALYTICAL TOOL
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In hospitals, managing crowd is a big issue. Particularly, in emergency departments create major negative consequences for patients. Emergency departments need to explore the use of innovative methods to improve the patient flow and prevent overcrowding. One

CARDIAC DISEASE RECOGNITION THROUGH DATA MINING TECHNIQUES
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Nowadays heart condition is taken into account one among the main causes in todays world. It cant be easily predicted by the medical doctors because it be a difficult task that demands expertise and better knowledge for prediction. theres tons of knowledge

Sales Forecasting of Promotion Activities Based on the Cross-Industry Standard Process for Data Mining of E-commerce Promotional Information and Support
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The purpose of the study is to analyze and forecast the effect of e-commerce promotional activities and sales volume, and improve the scientific and intelligent degree of enterprise management and decision-making through data mining and analysis. The short-term effect

Use of data mining algorithms chaid and cart in predicting egg weight from egg quality traits of indigenous free-range chickens in zambia
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This study aimed to evaluate the performance of data mining algorithms Chi-square Automatic Interaction Detector (CHAID) and Classification And Regression Tree (CART) in predicting egg weight from different egg quality traits such as egg length (EL), egg width

CARM: Context Based Association Rule Mining for Conventional Data
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1 Introduction It is an information age as all is transferred to computers and the use of the information system has become a necessity of life. Knowledge extraction from data takes place through the data mining process. Data

ANALYSIS OF DISCIPLINE LEVEL UNIVERSITY STUDENT ATTRITION USING DATA MINING
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Although most higher education institutes are experiencing high enrollments in Computer Science degree programmes, most students drop out before graduating. The impact of high attrition rates is severe, particularly for the small South Pacific Island nations where the

Co-clustering Numerical Data under User-defined Constraints STATISTICAL ANALYSIS AND DATA MINING (2010) 3
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In the generic setting of objects attributes matrix data analysis, co-clustering appears as an interesting unsupervised data mining method. A co-clustering task provides a bi-partition made of coclusters: each co-cluster is a group of objects associated to a group of attributes Executing the Apriori Hybrid Algorithm in Semi-structured Mining Datasets and Comparison with HD Algorithm D. Akila, S. Jeyalaksshmi, G. Suseendran, and D. Balaganesh Abstract The recent development in data mining in various fields and firms, for example, hospital

Using Unlabeled Data Set for Mining Knowledge from DDB
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Keywords: Knowledge Discovery in Databases (KDD); Data Mining (DM); Clustering Data Mining ; Classification Data Mining ; Distributed Database (DDB); Distributed Data Mining (DDM) This work is licensed under a Creative Commons Attribution-Share Alike 4.0

Modern Applications and Challenges for Rare Itemset Mining
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Page 1.  Abstract Data mining is the process of extracting useful unknown knowledge from large datasets. Frequent itemset mining is the fundamental task of data mining that aims at discovering interesting itemsets that frequently appear together in a dataset

River: machine learning for streaming data in Python
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Learning from time-changing data with adaptive win- dowing. In Proceedings of the SIAM international conference on data mining 443 448. SIAM In Proceedings of the SIAM international conference on data mining 328 339. SIAMThe in advance detection of cancer is not easier method but if it is detecte it is curable. Various works have been done in predicting lung cancer different data mining approach and algorithm were adopt by different people. All

Complete Closed Time Intervals-Related Patterns Mining
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Page 1. Complete Closed Time Intervals-Related Patterns Mining Omer Harel, Robert Moskovitch Software and Information Systems Engineering, Ben Gurion University of the Negev, Beer Sheva, Israel omerdavi@post.bgu.ac.il, robertmo@bgu.ac.il Abstract

The Analysis Of Opinions About Teaching Profession On Twitter Through Text Mining
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With this research, it is suggested to make analyses on social media platforms with other data mining techniques on the same subject or different subjects, to analyze the shares of institutions and to examine the sharing of the Ministry of National Education Keywords: Teaching




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