内容提示: Volume 55 Issue 3 (June 2021)353 RESEARCH ARTICLE Indian Journal of Agricultural Research, Volume 55 Issue 3: 353-358 (June 2021)Soil Data Analysis and Crop Yield Prediction in Data Miningusing R-ToolK. Samundeeswari, K. Srinivasan 1 10.18805/IJARe.A-5449A BSTRACTBackground: ...
The state-of-the-art data mining technologies, genetic programming, has been applied to develop depth varying thermal structure. The model results are verified by using field-monitoring data in the South China Sea.doi:10.1142/9789812702838_0210Vladan Babovic...
Predictive mobility support for QoS provisioning in mobile wireless environments IEEE J. Select. Area Commun. (2001) A. Nanopoulos, D. Katsaros, Y. Manolopoulos, Effective prediction of web user accesses: a data mining approach, in:... A. Nanopoulos et al. A data mining algorithm for gene...
Fig. 1. TOB optimized data matching methodology configured for predicting and data mining highly skewed carbon-flux (net ecosystem carbon exchange; NEE) datasets. TOB Stage 1 assesses data-record matches between records in small, evenly distributed subset designed to tune the algorithm with a larger...
Big data analysis is a data mining technique that can be used in many sectors – economic, industrial and commercial. Data mining can be defined as preparing, visualizing and exploring massive databases (Parr & Vaudrevange, 2020), whereas the techniques for discovering patterns from these ...
Classification in Large Databases Classification—a classical problem extensively studied by statisticians and machine learning researchers Scalability: Classifying data sets with millions of examples and hundreds of attributes with reasonable speed Why decision tree induction in data mining? relatively faster ...
The Elements of Statistical Learning: Data Mining, Inference, and Prediction Second Edition Trevor Hastie Robert Tibshirani Jerome Friedman Springer,2008 内容简介 During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a...
To keep current clients, a corporation needs to analyze data in the customer database to determine the reasons for their departure2. The basic goal of customer churn prediction is to identify customers who are likely to leave the company. Avoiding client churn has become a critical goal for ...
Data mining Machine learning This article is cited by Machine Learning-Assisted Low-Dimensional Electrocatalysts Design for Hydrogen Evolution Reaction Jin Li Naiteng Wu Qiaobao Zhang Nano-Micro Letters (2023) Machine learning in concrete science: applications, challenges, and best practices Zhanzh...
It is a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting--...