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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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Teaching Learning Based Optimization Algorithm | TLBO Numerical Example|

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Teaching Learning Based Optimization Algorithm

 | TLBO Numerical Example |

Learn Teaching Learning Based Optimization Algorithm Step-by-Step with Numerical Example.

Teaching Learning Based Optimization Algorithm is based on the effect of Teacher on the Learners in the class. Teaching Learning Based Optimization Algorithm is basically inspired by the behavior of learners in the classroom. In Teaching Learning Based Optimization Algorithm 2 main procedure are followed:

  1. Teaching Phase: Learners study from the Teacher.
  2. Learner Phase: Learners can interact with each other and they can randomly interact with each other.
Teaching Learning Based Optimization Algorithm Steps:
  1. Population Initialization Phase.
  2. Agents Performance Evaluation using Cost Function.
  3. Select Best Solution Among all.
  4. Calculate Mean Value.
  5. Teacher Phase.
  6. Mathematical Model
  7. Learner Phase
  8. MathematicalModel
  9. Evaluate New Solutions.
  10. Update Current Best Solution.
  11. Check Stopping Criteria.
  12. Display Best Solution.




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