Data Mining was a basic technique for examine the data in a choice of perception and categorizes it and finally to compress it. Classification was used to expect cluster relationship for data instances in data mining. Many key types of classification techniques including KNN, Bayesian classification, and Decision tree (DT) induction, C4.5, ID3, SVM, and ANN are used for classification. The majo...

AC Accuracy ADL Activities of daily living AF Average F-measure CNN Convolutional neural network CPU Central processing unit DBN Deep belief network DT Decision tree HA Hand Gesture HAR Human activity recognition KNN K-nearest neighbors LSTM Longand short-term memory MV Means and variance NB Naive Bayes NF Normalized F-measure OAR Opportunity activity recognition RAM Random access memory ReLU R...

Data mining term is mainly used for the specific set of six activities namely Classification, Estimation, Prediction, Affinity grouping or Association rules, Clustering, Description and Visualization. The first three tasks classification, estimation and prediction are all examples of directed data mining or supervised learning. Decision Tree (DT) is one of the most popular choices for learning ...

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The paper proposes a solution for the problem of optimizing medium voltage power systems which supply, among others, nonlinear loads. It is focused on decision tree (DT) application sizing and allocation active filters (APFs), are most effective means quality improvement. Propositions some DT strategies followed by results have been described in paper. On basis an example medium-voltage network...

A wormhole attack is a type of on the network layer that reflects routing protocols. The classification performed with several methods machine learning consisting K -nearest neighbor (KNN), support vector (SVM), decision tree (DT), linear discrimination analysis (LDA), naive Bayes (NB), and convolutional neural (CNN). Mo...

In this paper, we propose a piecewise linear decision tree and its generalized form, namely the (G)PWL-DT, which introduces linearity overcomes discontinuity of existing constant trees (PWC-DT). The proposed (G)PWL-DT inherits basic topology interpretability by recursively partitioning domain into subregions, are represented leaf nodes. Rather than indicator function, employs rectifier units (R...

Statistical features are widely used in radiology for tumor heterogeneity assessment using magnetic resonance (MR) imaging technique. In this paper, feature selection based on decision tree is examined to determine the relevant subset of glioblastoma (GBM) phenotypes in the statistical domain. To discriminate between active tumor (vAT) and edema/invasion (vE) phenotype, we selected the signific...

Covid-19, a contagious disease, has been classified as global pandemic. Indonesia, one of the ASEAN countries, taken various measures to combat spread this disease. One government's initiatives tackle pandemic is PeduliLindungi application, through which public provides feedback on government policies. However, analyzing and comprehending opinions in non-subjective manner poses challenge object...

Big data is usually unstructured, and many applications require the analysis in real-time. Decision tree (DT) algorithm widely used to analyze big data. Selecting optimal depth of DT time-consuming process as it requires iterations. In this paper, we have designed a modified version (DT). The aims achieve by self-tuning running parameters improving accuracy. efficiency was verified using two da...