Hello Everyone,

I would like to build a 2 dimensionnal mapping from numeric pairs of data (x,y) measurements to extract a pair of measured values X,Y. Physically I use a pair of independant sensors x and y which value depends on two physical parameters X and Y. I want to evaluate the X,Y value based on the sensor output (x,y). I tried an analytic approach but I am curious to check what a neural net or other machine learning method can produce... Unfortunately I am such noob in Mathematica Machine Learning features that the most intuitive syntax did not work and I am lost in the huge documentation stack. A little help to solve this problem would be appreciated. I put the input data with desired output in the following set:

In[338]:= dataset

Out[338]= {{68.6309, 129.667} -> {2.5, 3.1}, {70.2941, 
   99.9095} -> {2., 5.2}, {113.909, 321.53} -> {6., 2.8}, {142.928, 
   232.101} -> {4.5, 5.1}, {55.3224, 238.227} -> {5.5, 1.5}, {119.522,
    208.819} -> {4., 4.4}, {150.741, 261.237} -> {5., 4.7}, {41.072, 
   111.443} -> {4., 0.8}, {84.092, 236.134} -> {4.5, 2.5}, {48.7884, 
   135.185} -> {3., 1.5}, {43.5032, 160.155} -> {5., 1.}, {74.889, 
   129.237} -> {2.5, 3.7}, {50.9653, 99.9456} -> {2., 2.1}, {68.9513, 
   100.215} -> {2., 4.8}, {123.316, 322.451} -> {6., 3.}, {119.153, 
   176.668} -> {3.5, 5.7}, {107.202, 294.082} -> {5.5, 2.8}, {64.871, 
   220.448} -> {4.5, 1.9}, {38.7254, 50.6979} -> {5., 0.2}, {189.644, 
   310.274} -> {6., 5.3}, {38.6468, 48.4711} -> {2.5, 0.1}, {57.1366, 
   225.476} -> {5., 1.6}, {61.1515, 102.059} -> {2., 3.3}, {85.6425, 
   125.906} -> {2.5, 5.3}, {104.585, 150.047} -> {3., 6.}, {38.7243, 
   50.7576} -> {5.5, 0.2}, {42.4376, 166.234} -> {6., 0.9}, {182.675, 
   280.109} -> {5.5, 5.8}, {61.4204, 215.622} -> {4.5, 1.8}, {85.9459,
    156.648} -> {3., 3.7}, {153.129, 259.867} -> {5., 4.8}, {157.689, 
   290.152} -> {5.5, 4.4}, {40.3509, 72.9105} -> {2., 0.8}, {138.715, 
   323.33} -> {6., 3.4}, {135.675, 234.858} -> {4.5, 4.6}, {38.9446, 
   58.2436} -> {2.5, 0.4}, {170.61, 285.175} -> {5.5, 5.}, {41.1801, 
   146.194} -> {6., 0.8}, {50.4667, 189.199} -> {4.5, 1.4}, {155.337, 
   290.8} -> {5.5, 4.3}, {85.4773, 125.797} -> {2.5, 5.2}, {65.5635, 
   154.854} -> {3., 2.4}, {160.191, 257.469} -> {5., 5.3}, {50.2766, 
   156.212} -> {3.5, 1.5}, {184.011, 311.758} -> {6., 5.}, {97.224, 
   184.132} -> {3.5, 3.7}, {132.302, 235.906} -> {4.5, 4.4}, {93.617, 
   239.2} -> {4.5, 2.8}, {180.038, 281.284} -> {5.5, 5.6}, {84.092, 
   236.134} -> {4.5, 2.5}, {41.2955, 89.0044} -> {2.5, 0.9}, {162.174,
    256.902} -> {5., 5.4}, {41.65, 112.208} -> {3.5, 0.9}, {42.3083, 
   108.205} -> {3., 1.}, {90.6357, 155.272} -> {3., 4.1}, {111.265, 
   239.624} -> {4.5, 3.4}, {60.6884, 233.118} -> {5., 1.7}, {39.8793, 
   95.6126} -> {5., 0.6}, {50.4796, 233.256} -> {6., 1.3}, {43.4821, 
   114.843} -> {3., 1.1}, {119.153, 176.668} -> {3.5, 5.7}, {142.948, 
   263.592} -> {5., 4.3}, {185.97, 311.757} -> {6., 5.1}, {40.2314, 
   98.7904} -> {4., 0.7}, {102.905, 150.98} -> {3., 5.6}, {82.4606, 
   127.227} -> {2.5, 4.7}, {60.2038, 102.346} -> {2., 3.2}, {141.6, 
   232.627} -> {4.5, 5.}, {132.302, 235.906} -> {4.5, 4.4}, {139.056, 
   294.435} -> {5.5, 3.7}, {57.1366, 225.476} -> {5., 1.6}, {39.9041, 
   68.7561} -> {2., 0.7}, {39.7357, 91.0486} -> {4.5, 0.6}, {189.644, 
   310.274} -> {6., 5.3}, {76.1032, 128.777} -> {2.5, 3.8}, {126.486, 
   266.681} -> {5., 3.6}, {39.7658, 100.218} -> {5.5, 0.6}, {58.6326, 
   246.947} -> {5.5, 1.6}, {40.8331, 102.376} -> {3.5, 0.8}, {67.3071,
    202.198} -> {4., 2.1}, {38.8807, 54.7734} -> {3.5, 0.3}, {92.7047,
    155.039} -> {3., 4.3}, {46.183, 94.5789} -> {2., 1.6}, {107.202, 
   294.082} -> {5.5, 2.8}, {38.7246, 50.5458} -> {4., 0.2}, {53.5837, 
   101.482} -> {2., 2.4}, {51.6686, 208.37} -> {5., 1.4}, {148.376, 
   292.113} -> {5.5, 4.}, {119.153, 176.668} -> {3.5, 5.7}, {151.33, 
   228.195} -> {4.5, 5.8}, {182.737, 312.524} -> {6., 4.9}, {65.9409, 
   262.386} -> {5.5, 1.8}, {135.675, 234.858} -> {4.5, 4.6}, {38.8756,
    56.6874} -> {5.5, 0.3}, {49.0207, 98.1754} -> {2., 1.9}, {97.9427,
    152.873} -> {3., 4.9}, {41.4433, 80.3218} -> {2., 1.}, {46.0737, 
   111.286} -> {2.5, 1.4}, {130.595, 204.734} -> {4., 5.3}, {43.4189, 
   88.6406} -> {2., 1.3}}

For instance, in the training dataset member {68.6309, 129.667} -> {2.5, 3.1}, {68.6309, 129.667} is the (x,y) input and {2.5, 3.1} is the desired (X,Y) output.

Then when I apply Predict to this dataset I get the following error:

In[339]:= p = Predict[dataset]

During evaluation of In[339]:= Predict::mlincfttp: Incompatible variable type (Numerical) and variable value ({2.5,3.1}).

Can someone explain how I can get a pair of number when I enter a pair of numbers?

Thanks in advance

Christian