In this tutorial we are going to create and train Iris model using ANNdotNET. ANNdotNET is windows application for creating and training CNTK based models without leaving GUI.
All procedures from downloading the data set, to exporting model, can be achieved in 6 steps.
1. Step: Download the data set file from https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data.
2. Step: Open ANNdotNET application. Press New command, select Project 1 tree item and rename the project into Iris Data Set.
2. Step: Select Data Command from Model Preparation ribbon group, Click File button from Import experimenal data dialog and select the recently downloaded file. Check Comma check box and press Import Data button.
3. Steps: Double click on Scaling for each column, and select MinMax normalization option from the popup ComboBox list. Double click on Type for the output column, and select Category, and 1:N for encoding. More information how to prepare data for ML you can find at https://bhrnjica.net/2018/03/01/data-preparation-tool-for-machine-learning/
4. Steps: Once the data is prepared Click Create Model Command and Model Settings panel is shown. Setup parameters as shown on the image below and click Run command.
5. Steps: Once the model is trained you can evaluate model by selecting Evaluate Command. Depending on the model type (regression, Binary or Multi class classification) The appropriate Evaluation dialog appears. Since this is multi class classification model, the Confusion matrix is shows, with micro and macron performance parameters.
6. Steps: For further analysis you can export model to Excel, or into ONNX. Also you can save the project which can later be opened and retrained again.
Note: Currently ANNdotNET is in alpha version, and more feature will come in near future.