New Post

Confusion Matrix with Real-Life Examples || Artificial Intelligence || ~...

Image
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

Cuckoo Search Algorithm By Levy's Flight

Q. What is the Cuckoo Search Algorithm?
A. Cuckoo Search  Algorithm is a Meta-Heuristic Algorithm. Cuckoo Search  Algorithm is inspired by some Cuckoo species laying their eggs in the nest of other species birds. In this algorithm, we have 2 birds Species: Cuckoo birds and Host Birds (i.e., Other Species Bird). Cuckoo bird lay its eggs in the nest of other species birds. This increase their survival and productivity.

Q. What happened if Host Bird Discovered Cuckoo Egg? 
A. If Host Bird Discovered Cuckoo Bird Eggs:
        1.) The host bird can throw the egg away.
        2.) Abandon the nest and build a completely new nest.

Mathematically, Each egg represent a solution and it is stored in the host bird nest. In this algorithm Artificial Cuckoo Birds are used. Artificial Cuckoo can lay one egg at a time. We will replace New and better solutions with less fit solutions. It means eggs that are more similar to host bird has opportunity to develop in the new generation and become new cuckoo. In the population, number of host nest are fixed. If host bird discovered cuckoo egg consider this worst solution that is away from optimal value.
Consider, Cuckoo Egg = New Solution.
  and        Eggs in the nest = Set of Solutions.
  and    High Quality Eggs = Best Solutions that is near to the Optimal Solution.

Q. Explain the Cuckoo Search Algorithm Implementation Rules? 
  1. A. Each Cuckoo Lays only one Egg at a time and places it in a randomly selected nest.
  2. Best Nest with high quality of Eggs will carry over to the next generation.
  3. The number of available host nest is fixed. The host bird discovers cuckoo eggs with probability 𝑷a ϵ (0,1). Host birds can throw away the egg or leave nest/to build a new one.
Cuckoo Search Optimization Algorithm Steps:


For more Details: Cuckoo Search Algorithm Step-by-Step Explanation

Cuckoo search algorithm Application 

Training neural network.

Solve Nurse scheduling problem.

To solve the knapsack problem.

Traveling Salves man Problem.

 
#happyLearning #research #mathIsMagic 

Comments

Popular Post

PARTICLE SWARM OPTIMIZATION ALGORITHM NUMERICAL EXAMPLE

Cuckoo Search Algorithm for Optimization Problems

PSO (Particle Swarm Optimization) Example Step-by-Step

Particle Swarm Optimization (PSO)

how is the LBP |Local Binary Pattern| values calculated? Step-by-Step with Example

PSO Python Code || Particle Swarm Optimization in Python || ~xRay Pixy

Grey Wolf Optimization Algorithm

Bat algorithm Explanation Step by Step with example

Grey Wolf Optimization Algorithm Numerical Example

Whale Optimization Algorithm Code Implementation || WOA CODE || ~xRay Pixy