搜索资源列表
elm
- ELM对iris数据的分类，以及预测和训练。-ELM for iris data classification, and prediction and training.
chapter_07
- 通过几个特征对iris种类预测，机器学习，多元应用回归分析(iris prediction, using machine learning to analyse several characters to predict)
05第5章
- 时间序列，神经，灰色预测。 微分方程建模，差分运算(Time series, nerve, gray prediction. Differential equation modeling, differential operation)
RBF、GRNN和PNN神经网络案例
- 能够实现RBF,GRNN和PNN神经网络的案例，一个是RBF-近红外光谱汽油辛烷值预测，GRNN，PNN-鸢尾花种类识别。代码和数据均有，直接可以拿来使用。(These are cases of RBF, GRNN and PNN neural networks can be realized. One is RBF-NIR spectroscopy gasoline octane prediction, GRNN, PNN-Iris
SVM_tensorflow-master
- SVM通过tensorflow训练iris数据集，寻找最优参数，使误差最小化(SVM trains iris data set through tensorflow to find the optimal parameters and minimize the error.)
iris
- 使用鸢尾花数据集，通过神经网络算法对鸢尾花类型进行预测(Using iris data set, the iris type was predicted by neural network algorithm.)