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Confusion Matrix with Real-Life Examples || Artificial Intelligence || ~...

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Learn about the Confusion Matrix with Real-Life Examples. A confusion matrix is a table that shows how well an AI model makes predictions. It compares the actual results with the predicted ones and tells which are right or wrong. It includes True Positive (TP), False Positive (FP), False Negative (FN), and True Negative (TN). Video Chapters: Confusion Matrix in Artificial Intelligence 00:00 Introduction 00:12 Confusion Matrix 03:48 Metrices Derived from Confusion Matrix 04:26 Confusion Matrix Example 1 05:44 Confusion Matrix Example 2 08:10 Confusion Matrix Real-Life Uses #artificialintelligence #machinelearning #confusionmatrix #algorithm #optimization #research #happylearning #algorithms #meta #optimizationtechniques #swarmintelligence #swarm #artificialintelligence #machinelearning
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Metaheuristics Performance Comparison | PSO vs JAYA Algorithm | ~xRay Pixy

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Metaheuristics Performance Comparison Comparison of the Metaheuristic Algorithms Performances Video Chapters: Introduction: 00:00 Metaheuristic Algorithms Applications: 01:41 Metaheuristics Comparision: 02:43 Testing Parameters: 06:16 Testing Output: 07:24 Optimal Values: 09:00 Computation Time: 12:00 Conclusion: 13:20 Questions Answered in this Video: Which is the best metaheuristic algorithm? Learn how to Compare Metaheuristic Optimization Algorithms Performance using the Standard Test Functions. Standard Test Functions used for Testing: - Unimodel Test Functions - Multi-Model Test Functions Metaheuristics Algorithms used for Comparision: - Particle Swarm Optimization (PSO) Algorithm - Jaya Optimization Algorithm (JOA) Testing Output is checked based on: - Optimal Value - Computation Time Using these test functions we will analyze the algorithm's Stability, Convergence Speed, and Accuracy. The comparison between the two metaheuristics is done using the standard test functi...
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