Technical Details:
Model Class: MLPClassifier from scikit-learn.
Architecture Type: Fully Connected Dense Network-Every neuron in one layer connects to every neuron in the next layer
Input Layer:Size: a)Number of features in your dataset, b)Function: Receives raw feature data
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)
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)