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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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Soft Computing - Fuzzy Logic | Fuzzy Relations | DOM | FIS || Unit 1 || ...

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Learn Soft Computing Basics step-by-step using Example. Video Chapter: 00:00 Introduction 00:09 Topics Covered 02:13 What is Fuzzy Logic? 07:06 What is Crisp Set? 08:03 What is the Degree of Membership? 09:05 Fuzzy Logic Components 10:46 Fuzzy Logic Operators 11:47 Fuzzy Relations 15:03 Fuzzy Relation Composition 17:28 Fuzzy Inference System 17:52 Defuzzification What is a Crisp Set? A "crisp set" or "crisp logic" refers to the traditional, classical set theory and logic where elements either belong to a set or do not, with no in-between or degrees of membership. In crisp logic, membership is binary—something is either a member of a set (true) or not (false). What is a Fuzzy Logic? Fuzzy logic is a mathematical framework that deals with reasoning and decision-making in the presence of uncertainty and imprecision. Unlike classical (Boolean) logic, which is based on binary values (true or false, 0 or 1), fuzzy logic allows for the representation of parti...
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