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- | ====== Classification ====== | ||
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- | ===== 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// | ||
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- | ====== Regression ====== | ||
- | |||
- | * **MLP (Multi Layers Perceptron)** | ||
- | * **RBFNN (Radial Basis Functions Neural Network)** | ||
- | * **SVR (Support Vectors Regressor)** | ||