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| - | ====== Classification ====== | ||
| - | |||
| - | ===== MLP ===== | ||
| - | Multi Layers Perceptron, //PMC (Perceptron Multi-Couches)// | ||
| - | ====Gradient Backpropagation==== | ||
| - | // | ||
| - | ===Stochastic=== | ||
| - | ===with Inertia=== | ||
| - | ===Simulated Annealing=== | ||
| - | //Recuit Simulé// | ||
| - | |||
| - | ====newton==== | ||
| - | =Quick Def= | ||
| - | second order | ||
| - | |||
| - | =====RBFNN===== | ||
| - | Radial Basis Functions Neural Networks | ||
| - | * __k-means then gradient descent__ | ||
| - | * __incremental addition of neurons then exact method__ | ||
| - | |||
| - | =====SVM===== | ||
| - | Support Vectors Machine | ||
| - | |||
| - | =====Decision tree===== | ||
| - | //arbre de d�cision// | ||
| - | * __ID3__ (based on entropy) | ||
| - | |||
| - | =====k-nearest neighbors===== | ||
| - | //k plus proches voisins// | ||
| - | |||
| - | ====== Regression ====== | ||
| - | |||
| - | * **MLP (Multi Layers Perceptron)** | ||
| - | * **RBFNN (Radial Basis Functions Neural Network)** | ||
| - | * **SVR (Support Vectors Regressor)** | ||




