Breast cancer dataset

I have used Multi class neural networks for the prediction of type of breast cancer on other parameters. The full details about the Breast Cancer Wisconin data set can be found here - [Breast Cancer Wisconin Dataset][1]. I have used used different algorithms - ## 1. Neural Network - **Hyperparameters tuning** Single parameter trainer mode fully connected perceptron 200 perceptron learning rate - 0.001 learning iterations - 200 initial learning weights - 0.1 min-max normalizer shuffled examples Accuracy - 0.994048 ## 2.Multi class random forest - **Hyperparameter tuning** Single parameter training mode Resampling - bagging Decision trees - 15 Maximum depth - 32 Random splits per node - 128 Minimum samples per leaf node -1 Accuracy - 0.988095 So, I have used Multi class neural network which provides high accuracy. Dataset reference - UCI machine learning repository [1]: http://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+%28original%29