unable to use my own data like .xlsx, csv, and arff

First question:

[x,t] = house_dataset; net = feedforwardnet(10,'trainlm'); net = train(net,x,t); y = net(x) But, here i want to use my own data which is .xlsx format instead of house_dataset provided by matlab to train the feedforward neural network and then to predict. This .xlsx contains only numeric value.

here is my excel data. 12 row, 6 column data

44.38 44.57 44.05 44.28 10014700.00 44.28 44.60 44.76 44.26 44.45 9223800.00 44.45 43.21 44.72 43.21 44.43 17922900.00 44.43 43.45 43.52 42.91 43.38 9797500.00 43.38 43.99 43.99 43.42 43.53 12129100.00 43.53 44.30 44.36 43.76 44.11 12036200.00 44.11 43.65 44.42 43.50 44.37 13301000.00 44.37 43.56 43.82 43.30 43.65 10410700.00 43.65 44.37 44.54 43.35 43.53 12798400.00 43.53 44.12 44.59 44.00 44.42 13785800.00 44.42 43.07 44.16 42.86 43.93 18158200.00 43.93 43.18 43.26 42.76 42.96 9791100.00 42.96

I read it like num = xlsread('myExample.xlsx');

this is the result num =

   1.0e+07 *

    0.0000    0.0000    0.0000    0.0000    1.0015    0.0000
    0.0000    0.0000    0.0000    0.0000    0.9224    0.0000
    0.0000    0.0000    0.0000    0.0000    1.7923    0.0000
    0.0000    0.0000    0.0000    0.0000    0.9798    0.0000
    0.0000    0.0000    0.0000    0.0000    1.2129    0.0000
    0.0000    0.0000    0.0000    0.0000    1.2036    0.0000
    0.0000    0.0000    0.0000    0.0000    1.3301    0.0000
    0.0000    0.0000    0.0000    0.0000    1.0411    0.0000
    0.0000    0.0000    0.0000    0.0000    1.2798    0.0000
    0.0000    0.0000    0.0000    0.0000    1.3786    0.0000
    0.0000    0.0000    0.0000    0.0000    1.8158    0.0000
    0.0000    0.0000    0.0000    0.0000    0.9791    0.0000

and also Min max range 42.7600 18158200 1.8158e+07

and i assigned it to [x, t] = num

but the result is "Too many output argument"

Second question:

My data has 7 columns and 1500 rows including column name and one row of date data. how can i import this .xlsx data and predict new data with the next date for which the data is to be predicted for. Please help me

Answer 1

[Perry]

2 ways to import

go to 'file' then 'import' and you can do it there or use

num = xlsread( filename , sheet , xlRange , 'basic' ) (but data needs to be in your working directory otherwise you need to specify the path where to find it c:....

on the dataset and prediction i have no idea, but instead of working with neural networks i would first suggest you consider pcr or pls (pricipial component regression)

trialversion: eigenvector research: pls toolbox-no code needed, its a gui or u check out www.models.life.ku.dk its a collection of code for multivariate dataanalysis

u read your trainingdata into inputs

houseInputs=num;

and you read the data you wanne predict/classify to

houseTargest=....; % houstargets is just one row with 506 entries

then u start the NN gui with nnstart and follow the instruction and play around be aware of the fact that you cant be a master of stuff when u spend less time as possible on a subject, what i mean is question your results with common sense and try to reproduce and understand the tutorial

 http://www.mathworks.com/help/nnet/gs/fit-data-with-a-neural-network.html

hope it helps....

[Andualem alemu]

tnx. now I have updated my question with the data i am using. would you please help me on this one