… Concentrating on performance evaluation as we do in this paper, let us consider what happens
in one of the most common evaluation scenarios in machine learning: cross-validation of …

… different machine learning … machine learning techniques in intrusion detection is limited.
Hence this paper aims at understanding the implications of using supervised machine learning …

… of predictive models based on the four machine learning methods, namely Bayes Network,
Naïve … if a particular predictive model derived from machine learning methods aligns with their …

Grouping the objects based on their similarities is an important common task in machine
learning applications. Many clustering methods have been developed, among them k-means …

… of six machine learning techniques was evaluated for prediction of heart disease. The
recital of these methods was assessed on eight diverse classification performance indices. In …

… a classification and performance evaluation framework … machine learning algorithms in the
context of an object-based image analysis and to thoroughly test the algorithm’s performance …

… Most of these works are utilizing machine learning algorithm to separate spam and nonspam…
, there lacks of a performance evaluation of existing machine learning-based streaming …

… study compares RF with other machine learning models, such as DT, SVM, LR and NN. The
experimental results illustrate that RF has the best performance on classification accuracy in …

… In the experiments, four well-known machine learning algorithms are used, namely Naïve
Bayes, Decision Tree, and Random Forest are used for performance evaluation. …

… machine learning and deep learning techniques for diabetes prediction and measure the
performance of … In this context, Convolution neural network (CNN) gives better performance as …