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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

Bacterial Foraging Optimization Algorithm (BFOA) Step-by-Step Learning ~...

Bacterial Foraging Optimization Algorithm (BFOA) 


Bacterial Foraging Optimization Algorithm is a recently developed nature-inspired optimization algorithm, which is based on the foraging behavior of Escherichia coli or E. coli bacteria.

Bacterial Foraging Optimization Algorithm Advantages:
1.) Used to solve Engineering Problems.
2.) Used to Solve complex real world Optimization Problems.

About Escherichia coli or E. coli bacteria.
Escherichia coli or E. coli bacteria lives in our intestine and they are also found in the gut of some animals. Most of the Escherichia coli or E. coli bacteria are harmless. But some can cause Diarrhoea, if you eat contaminated food or drink fouled water. Escherichia coli or E. coli bacteria is mainly associated with Food positioning, Urinary Tract Infection (UTI) - approximate 75%-95% UTI are caused by Escherichia coli or E. coli bacteria. Escherichia coli or E. coli bacteria causes certain symptom's: Vomiting's, Confusion, Diarrhoea, Abdominal Cramps, Kidney Failure in kids as well as in Adult and Fever.

Bacterial Foraging Optimization Algorithm: KEY IDEA
Bacterial Foraging Optimization Algorithm is basically inspired by group foraging strategy of E. Coli Bacteria. Bacteria search for nutrients in order to maximize their energy and they can also communicate with each other by sending signals. Bacterial Foraging Optimization Algorithm mimic the Chemotactic movement of virtual bacteria's in the search space.

Bacterial Foraging Optimization Algorithm 4 main steps:
1.) Chemotaxis
2.) Swarming
3.) Reproduction
4.) Elimination and Dispersal

Video Timestamps:
Introduction: 00:00 Escherichia coli Bacteria: 00:38 BFOA Key Idea: 01:19 Bacterial Foraging Optimization Algorithm Pseudocode: 08:05 Conclusion: 10:30





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