In subject area:Computer Science A Data Mining Algorithm is a logical step-by-step procedure used in data mining to solve specific data problems. These algorithms can be recursive, contain random variables, and are chosen based on factors like data set type, objective, and computational resources...
- 《Arabian Journal for Science & Engineering》 被引量: 8发表: 2016年 Geometric mean based boosting algorithm with over-sampling to resolve data imbalance problem for bankruptcy prediction In classification or prediction tasks, data imbalance problem is frequently observed when most of instances belong...
Clustering is a form of learning by observations. It is an unsupervised learning method and does not require training data set to generate a model. Clustering can lead to the discovery of previously unknown groups within the data. It is a common method of data mining in which similar and d...
With a high priority in database development and application, database query algorithm is especially important for complex data processing in deep level. Aiming at accomplishing queries for multi-level users, a new iterative query algorithm is proposed on top of the recursive algorithms. This algorit...
VijayKotu,BalaDeshpande, inData Science (Second Edition), 2019 Abstract In classification or class prediction, it’s best to try to use the information from the predictors or independent variables to sort adata sampleinto two or more distinct classes or buckets. Classification is the most widely...
As an interdisciplinary research discipline that includes big data, machine learning, graph theory, and other disciplines, network science provides a new perspective and method for the study of complex systems in nature and society. The classification and recognition algorithm proposed in this study is...
In this article Azure Machine Learning Algorithm Cheat Sheet Data science scenario requirements Related content If you're wondering which machine learning algorithm to use, the answer depends primarily on two aspects of your data science scenario: ...
9 that the detection accuracy of the Optimized tiny YOLOv3 algorithm proposed in this paper for trunk, spherical tree and person is improved by 8.03%, 7.04% and 8.34% respectively compared with the original tiny YOLOv3. The mAP value has improved significantly, increasing by 7.8%. The data ...
Machine learning for internet of things data analysis: a survey Mohammad Saeid Mahdavinejad, ... Amit P. Sheth, in Digital Communications and Networks, 2018 5 Taxonomy of machine learning algorithms Machine learning is a subfield of computer science, and is a type of Artificial Intelligence (AI...
Deep learning (DL) based detection models are powerful tools for large-scale analysis of dynamic biological behaviors in video data. Supervised training of a DL detection model often requires a large amount of manually-labeled training data which are time-consuming and labor-intensive to acquire. ...