Educational Data Mining
Data mining methods and techniques are applied to educationally related data as part of the burgeoning field known as educational data mining (EDM). Education data mining is the name of an emerging multidisciplinary research field that applies data mining…
Agriculture Data Feature Extraction Using Sequential Pattern Mining and Random Forest (SPM-RF) Data Mining Method
Feature extraction assumes a critical part in analyzing agricultural datasets and acquiring experiences for decision-making. In this paper we propose a methodology that consolidates Sequential Pattern Mining (SPM) and Random Forest (RF) techniques for feature…
Survey on Fruit Disease Identification in Agriculture Using Data Mining
Rathamani, M.; Kanjana Devi, P.
The field of agriculture needs to manage a lot of data and processing and recovery of significant data from this abundance of agricultural information is necessary to support the farmers. In this way, proper strategies and techniques are required for…
A Review of Data Mining Techniques for Enhancing Energy Efficiency in IoT Systems
…of Internet of Things (IoT) technologies has led to an unprecedented surge in data generation and energy consumption, raising concerns about sustainability and operational efficiency. This review explores the role of data mining techniques in…
Analysis and Survey on Fruit Disease Identification in Agriculture Using Data Mining
Rathamani, M.; Kanjana Devi, P.
…will be extremely valuable for the farmers to detect the disease in beginning time. Data mining is the process of discovering and extracting of intriguing patterns and knowledge from a lot of data. There are various data mining strategies to anticipate the…
Performance Evaluation of Player Performance Prediction Models Using Data Mining Techniques
…the performance evaluation of player performance prediction models using various data mining techniques, focusing on the application of machine learning algorithms to predict individual and team performance in sports. The study compares the effectiveness…
Fruit Disease Identification Using Feature Extraction and Data Mining
Rathamani, M.; Kanjana Devi, P.
Agriculture is one of the fields which produce data continually ensuring each of the four characteristics with fantastic development. There are various difficulties in preparing farming records which manages assortment of organized and unstructured…
A Review on Datamining in Agriculture
In this paper the makers present irrefutably the most used data mining strategies in the field of agriculture. A bit of these strategies, for example, the k-means, the k nearest neighbor, artificial neural networks and support vector machines, are talked…
Enhanced Back Propagation Neural Network for Fruit Disease Prediction and Classification
Rathamani, M.; Kanjana Devi, P.
Data mining assumes an essential part in the dynamic cycle in numerous application territories. Information mining is essential for data handling and the executives. Plant sicknesses bargain efficiency which impacts public activity and economy of the country.…
Hybrid Artificial Neural Network and Case Based Reasoning (Hanncbr) Classification Model for Classification of Agriculture Data in Different Area
…The advances in computing and information storage have given tremendous measures of data. The test has been to remove knowledge from this raw data that has lead to new strategies and techniques, for example, data mining that can connect the knowledge gap.…
Implementation of Different Approaches Using Enhanced Algorithms for Fruit Disease Identification
Rathamani, M.; Kanjana Devi, P.
…makes it hard to adjust the current industrial algorithms to the agricultural space.Data Mining procedures in horticulture field diverse data mining procedures are in use, for example, K-Means, K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN) and…
A Survey on Datamining in Agriculture
…can hurt the vegetation and diminish the yield. This paper gives audit of different data mining procedures utilized on agriculture soil dataset for compost suggestion. Basically I zeroed in on different soil boundaries like Fe, S, Zn, Cu, N and Ph esteem…
Data Preprocessing Using Enhanced Principal Component Analysis (EPCA) for Agricultural Datasets
Data pre-processing is considered as the core stage in core and data mining. Standardization, discretization, and dimensionality decrease are notable strategies in data pre-processing. In this paper proposed Enhanced Principal component Analysis (EPCA) the…
Analysis of Heart Diseases Dataset Using Neural Network Approach
One of the important techniques of Data mining is Classification. Many real-world problems in various fields such as business, science, industry and medicine can be solved by using classification approach. Neural Networks have emerged as an important tool for…
Fruit Grade Classification Using Improved Convolutional Neural Network
Rathamani, M.; Kanjana Devi, P.
…end too. This can be achieved by implementing the image processing techniques and data mining techniques. The image datasets are collected from various online resources. The datasets are collected and examined based on the size, shape, texture and color…
Export this page’s citations: RIS (Zotero, Mendeley, EndNote) BibTeX