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浅层神经网络的样本数据集

Deep Learning Toolbox™ 包含许多样本数据集,您可以使用这些数据集来试验浅层神经网络。要查看可用的数据集,请使用以下命令:

help nndatasets
  Neural Network Datasets
  -----------------------
 
  Function Fitting, Function approximation and Curve fitting.
 
  Function fitting is the process of training a neural network on a
  set of inputs in order to produce an associated set of target outputs.
  Once the neural network has fit the data, it forms a generalization of
  the input-output relationship and can be used to generate outputs for
  inputs it was not trained on.
 
   simplefit_dataset     - Simple fitting dataset.
   abalone_dataset       - Abalone shell rings dataset.
   bodyfat_dataset       - Body fat percentage dataset.
   building_dataset      - Building energy dataset.
   chemical_dataset      - Chemical sensor dataset.
   cho_dataset           - Cholesterol dataset.
   engine_dataset        - Engine behavior dataset.
   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

请注意,所有数据集的文件名均为 name_dataset 格式。这些文件中将包含数组 nameInputsnameTargets。您可以使用如下命令将数据集加载到工作区中:

load simplefit_dataset

这会将 simplefitInputssimplefitTargets 加载到工作区中。如果要将输入数组和目标数组加载为不同名称,可以使用如下命令:

[x,t] = simplefit_dataset;

这会将输入和目标分别加载到数组 xt 中。您可以使用如下命令获取数据集的说明:

help maglev_dataset