okankeles / flower-classification

a C# project that classifies flowers from the Iris dataset using a simple neural network.

Flower Classification (Cicek Siniflandirma)

Flower Classification is a C# project that classifies flowers from the Iris dataset using a simple neural network. The project reads data from the iris dataset, scales the input values, initializes weights, and trains the network using different learning rates and epoch counts. The main functionalities of the project include:

• Loading Dataset: Reads and parses the Iris dataset from the embedded resources.
• Data Scaling: Scales input features to the 0-1 range.
• Weight Initialization: Randomly initializes the weights of the neurons.
• Training: Trains the neural network with various learning rates and epoch counts, adjusting weights based on the error.
• Testing: Tests the trained network and outputs the classification accuracy.

The project demonstrates basic neural network operations and can serve as a foundation for learning neural network implementation in C#.