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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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Shuffled Frog Leaping Algorithm (SFLA) Step-by-Step with Example ~xRay Pixy

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Shuffled Frog Leaping Algorithm (SFLA)  Video Timestamps: Introduction: 00:00 Shuffled Frog Leaping Algorithm (SFLA) Steps: 00:46 Shuffled Frog Leaping Algorithm (SFLA) Example: 02:00 Conclusion: 06:30 There are over 6000 different species of frogs. Frogs are found all over the world expect Antarctica. Shuffled Frog Leaping Algorithm (SFLA) is an Nature Inspired Swarm Based Metaheuristic Optimization Algorithm. Shuffled Frog Leaping Algorithm (SFLA) is inspired by frogs behavior. Shuffled Frog Leaping Algorithm (S.F.L.A.) is proposed by Eusuff and Lansey in 2003. To determine the optimum size of New Pipes (in the development of Network of pipes). Shuffled Frog Leaping Algorithm is basically inspired by the frogs behavior in finding food in the wetlands. Shuffled Frog Leaping Algorithm is combination of PSO and Memetic Algorithm. In Shuffled Frog Leaping Algorithm (S.F.L.A.), Population is Groups of Frogs and e ach Frog: Solution / Answer for the given problem. Shuffled Frog L...
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