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Hidden Markov Model (HMM)

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Hidden Markov Model (HMM)  VIDEO LINK:  https://youtu.be/YIGCWNG8BIA A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. Video Chapters: HMM in Artificial Intelligence 00:00 Introduction 00:31 Statistical Model 00:54 HMM Examples 02:30 HMM 03:10 HMM Components 05:23 Viterbi Algorithm 06:23 HMM Applications 06:38 HMM Problems 07:28 HMM in Handwriting Recognition 11:20 Conclusion  HMM COMPONENTS A Hidden Markov Model (HMM) is a statistical model in which the system has hidden states that cannot be directly observed, but produce observable outputs. It is based on the Markov property, meaning the next state depends only on the current state. An HMM consists of states, observations, transition probabilities, emission probabilities, and initial probabilities. It is commonly used in a...

Software Testing using Metaheuristic Optimization Algorithms

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Q. Where we can use Metaheuristic Optimization Algorithms? A. Metaheuristic Algorithms are used in different fields to solve optimization problems in different fields either for minimization of for maximization.  Metaheuristic Algorithms Categories.  1. Single Based Metaheuristic Algorithms: Single Solution is generated at each iteration/generation. Single Based Metaheuristic Algorithms Examples. Tabu Search Guided Local Search Iterated Local Search Variable Neighborhood Search Greedy Randomized Adaptive Search 2. Population-Based Metaheuristic Algorithms: Multiple Solutions are generated at each iteration/generation. Examples: Nature-Inspired Metaheuristic Algorithm      Evolutionary Algorithms Swarm Based Algorithm Human-Based Algorithm  Physics-Based Algorithm Bio-Inspired Algorithm Art-Inspired Algorithm Plant-Based Algorithm Q. How we can use Metaheuristic Optimization Algorithms in Software Testing? Metaheuristic Optimization Algorithm in Software Te...
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