Applications of Data Mining Techniques in Prediction of Heart Attacks Using Naive Bayes and Rule Based Classification AlgorithmKnowledge discovery and data mining have found numerous applications in business and scientific domain. Valuable knowledge can be discovered from application of data mining techniques...
Ischemic, one of the fatal diseases characterized by insufficient blood supply to tissues poses a significant global health burden, necessitating the devel
In this section, we propose Algorithm 1 as a wrapper for selecting features in vine copula-based classifiers. We assume that each variable has been transformed to remove extreme skewness (and orders of magnitude variability) before exploratory data analysis and applications of classification methods. ...
Clustering is a fundamental concept in data mining, which aims to identify groups or clusters of similar objects within a given dataset. It is adata miningalgorithm used to explore and analyze large amounts of data by organizing them into meaningful groups, allowing for a better understanding of ...
Gaussian mixture models via expectation-maximization algorithm Density-based clustering Density-based spatial clustering of applications with noise (DBSCAN) Ordering points to identify the clustering structure (OPTICS) Mean-shift Canapoy Association rule learning Apriori Eclat Topic modeling (text data)...
Optimization Naive Bayes Algorithm Using Particle Swarm Optimization in the Classification of Breast Cancer Vira MELINDA, Rifkie PRIMARTHA, Adi WIJAYA, Muhammad Ihsan JAMBAK Methods of data mining classification are used in various fields of research. Naive Bayes is one of the most used algorithms of...
One commonly used algorithm is Logistic Regression, particularly in fraud detection. Logistic regression calculates the probability that a transaction is fraudulent based on various features like transaction amount and user behavior. If the probability exceeds a particular threshold, the transaction is flagg...
Moreover, the losses that are present in this type of system are reduced even if the data is stored in the cloud. Furthermore, volume of information in presence of large data set is prevented using machine learning algorithm where ten initial attributes are completely knowledgeable; thus, it ...
Algorithmic trading aims to replace human trader with an algorithm running on a computer system. Algorithmically generated trade, in theory, can generate profits at a speed that is impossible for a human trader. High frequency trading is a sub-class of algorithmic trading. HFT requires the lowest...
Effect of k-NN algorithm Our proposed tool is developed based on the GCN framework by graph sampling with the feature and topology graph. The k-Nearest Neighbor (k-NN) algorithm is used to construct a full graph based on node features and network topology. For each target node, the k mos...