Multi-Layer Perceptron (MLP)@ Feedforward NN

Technical Details:

1. Model Class: MLPClassifier from scikit-learn.

2. Architecture Type: Fully Connected Dense Network-Every neuron in one layer connects to every neuron in the next layer

3. Input Layer:Size:  a)Number of features in your dataset, b)Function: Receives raw feature data

4. Hidden Layer(s): a) Count: 1-50 layers (user configurable), b) Size: 64 neurons per layer (fixed), c) Activation: ReLU, Tanh, or Logistic (user choice)

5. Output Layer: a) Size: Number of classes in target variable, b) Activation: Automatically chosen based on problem type, c) Binary classification: Logistic/Sigmoid, d) Multi-class: Softmax

🎯 Problem Types It Solves:

Classification Tasks:

✅ Binary Classification (2 classes)

✅ Multi-class Classification (3+ classes)