DCOM 212 Chapter 13 Quiz correctly answered rated A+

DCOM 212 Chapter 13 QuizLearning models with associated learning algorithms that analyze data & recognition patterns A.) Naïve Bayes Classifier B.) Decision Tree C.) Support Vector Machine (SVM) D.) Neural Networks .E.) Fuzzy Logic [Fuzzy Intrusion Recognition Engine (FIRE)] - correct answer C.) Support Vector Machine (SVM) A simple probabilistic classifier based on applying Bayes' theorem with strong innocent minded independence. A.) Decision Tree B.) Support Vector Machine (SVM) C.) Neural Networks D.) Naïve Bayes Classifier E.) Fuzzy Logic [Fuzzy Intrusion Recognition Engine (FIRE)] - correct answer D.) Naïve Bayes Classifier Objective leads is to combine several learning techniques A.) Hybrid Classifiers B.) Genetic Algorithms (GA) C.) K-Nearest Neighbor Classifier D.) Intrusion Detection E.) Specification-based detection - correct answer A.) Hybrid Classifiers Heuristic search that mimics the process that starts by randomly generating a large populations of candidate programs & is an iterative process A.) Genetic Algorithms (GA) B.) Specification-based detection C.) Hybrid Classifiers D.) K-Nearest Neighbor Classifier E.) Intrusion Detection - correct answer A.) Genetic Algorithms (GA) True or False? Unsupervised Learning Techniques provides an error and/or reward signal to evaluate a potential solution. - correct answer False Classifies a sample through a sequence of decisions, in which the current decision helps to make the subsequent decision A.) aïve Bayes Classifier Fuzzy Logic [Fuzzy Intrusion Recognition Engine (FIRE)] Decision Tree Neural Networks Support Vector Machine (SVM) - correct answer C.) Decision Tree Intrusion Detection is the process of monitoring the events occurring in a computer system of network & analyzing them for signs of possible incidents that violate computer security policies or standard security practices. True False - correct answer True Traditional non-parametric techniques to classify objects based on the closest training examples in the feature space Genetic Algorithms (GA) K-Nearest Neighbor Classifier Intrusion Detection Hybrid Classifiers Specification-based detection - correct answer K-Nearest Neighbor Classifier