神经网络数据集-----------------------函数拟合，函数逼近和曲线拟合。函数拟合是在一组输入上训练神经网络以产生一组相关的目标输出的过程。一旦神经网络拟合了数据，它就形成了输入-输出关系的泛化，并可用于为未经过训练的输入生成输出。simplefit_dataset -简单拟合数据集。abalone_dataset -鲍鱼壳环数据集。bodyfat_dataset -体脂百分比数据集。building_dataset -建筑能源数据集。chemical_dataset化学传感器数据集。cho_dataset -胆固醇数据集。engine_dataset -引擎行为数据集。 vinyl_dataset - Vinyl bromide dataset. ---------- Pattern Recognition and Classification Pattern recognition is the process of training a neural network to assign the correct target classes to a set of input patterns. Once trained the network can be used to classify patterns it has not seen before. simpleclass_dataset - Simple pattern recognition dataset. cancer_dataset - Breast cancer dataset. crab_dataset - Crab gender dataset. glass_dataset - Glass chemical dataset. iris_dataset - Iris flower dataset. ovarian_dataset - Ovarian cancer dataset. thyroid_dataset - Thyroid function dataset. wine_dataset - Italian wines dataset. digitTrain4DArrayData - Synthetic handwritten digit dataset for training in form of 4-D array. digitTrainCellArrayData - Synthetic handwritten digit dataset for training in form of cell array. digitTest4DArrayData - Synthetic handwritten digit dataset for testing in form of 4-D array. digitTestCellArrayData - Synthetic handwritten digit dataset for testing in form of cell array. digitSmallCellArrayData - Subset of the synthetic handwritten digit dataset for training in form of cell array. ---------- Clustering, Feature extraction and Data dimension reduction Clustering is the process of training a neural network on patterns so that the network comes up with its own classifications according to pattern similarity and relative topology. This is useful for gaining insight into data, or simplifying it before further processing. simplecluster_dataset - Simple clustering dataset. The inputs of fitting or pattern recognition datasets may also clustered. ---------- Input-Output Time-Series Prediction, Forecasting, Dynamic modeling Nonlinear autoregression, System identification and Filtering Input-output time series problems consist of predicting the next value of one time series given another time series. Past values of both series (for best accuracy), or only one of the series (for a simpler system) may be used to predict the target series. simpleseries_dataset - Simple time series prediction dataset. simplenarx_dataset - Simple time series prediction dataset. exchanger_dataset - Heat exchanger dataset. maglev_dataset - Magnetic levitation dataset. ph_dataset - Solution PH dataset. pollution_dataset - Pollution mortality dataset. refmodel_dataset - Reference model dataset robotarm_dataset - Robot arm dataset valve_dataset - Valve fluid flow dataset. ---------- Single Time-Series Prediction, Forecasting, Dynamic modeling, Nonlinear autoregression, System identification, and Filtering Single time series prediction involves predicting the next value of a time series given its past values. simplenar_dataset - Simple single series prediction dataset. chickenpox_dataset - Monthly chickenpox instances dataset. ice_dataset - Global ice volume dataset. laser_dataset - Chaotic far-infrared laser dataset. oil_dataset - Monthly oil price dataset. river_dataset - River flow dataset. solar_dataset - Sunspot activity dataset