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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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Genetic Algorithm In Hindi ~xRay Pixy

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Transient Search Optimization Algorithm || Step-By-Step || ~xRay Pixy https://youtu.be/T2lVQ8mYFoM Video Chapters: TSO Algorithm 00:00 Introduction 00:44 Topics Covered 01:14 Transient Behavior 02:57 Transient Search Optimization Algorithm 06:10 TSOA Mathematical Models 10:30 TSOA Step-By-Step 15:32 TSOA Applications 15:58 TSOA Advantages 16:22 TSOA Disadvantages 16:28 Conclusion Evolutionary algorithms (EAs) are optimization methods inspired by the process of evolution in nature. They aim to find the best solutions to problems by mimicking natural selection and genetics. Key Steps in Evolutionary Algorithms : Start with a Population: Think of a population as a group of random guesses or potential solutions to your problem. Each "individual" in the population represents one solution. Evaluate Fitness: Just like in nature, some individuals are better suited to survive in their environment. In EAs, the "fitness" of a solution tells us how good it is at solving the pr...
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