Hi Lars
Thanks a lot for the help so far.
It seems that your method solves part of my troubles. In my case X contains all
lines that are not NegCtrl and y the NegCtrl. Currently I am just trying to
load the sets into bumpy arrays and run something from the initial tutorial on
scikit-learn just to see if it works:
clf =svm.SVC(gamma=0.001, C=100.)
clf.fit(data[:-1], target[:-1])
When I run my scripts I get the data and target shapes as:
(179, 205)
(53, 205)
but I still get an error at the end when trying to fit the data
Traceback (most recent call last):
File "read.py", line 46, in <module>
clf.fit(data[:-1], target[:-1])
File "/Library/Python/2.7/site-packages/sklearn/svm/base.py", line 166, in fit
(X.shape[0], y.shape[0]))
ValueError: X and y have incompatible shapes.
X has 178 samples, but y has 10660.
Any further help is appreciated.
Thanks
Paulo
On 2013-05-18, at 8:02 AM, Lars Buitinck <[email protected]> wrote:
> 2013/5/18 Paulo Nuin <[email protected]>:
>> Drp1 41 1.91457014241 0.251069883932 103.0949514
>> 0.147634342712 1.75424087726 0.391473420716 0.
>
> If you get rid of the extra 0. at the end of this line, which I'm
> assuming is a mistake, then you can use np.genfromtxt [1] to easily
> load this file.
>
> with open("inputfile.txt") as infile:
> data = np.genfromtxt((ln for ln in infile if not
> ln.startswith("NegCtrl")), skip_header=1)
> data = data[:, 2:]
>
>> But when I do this I get a ValueError that X and y have incompatible shapes.
>
> What in this table is X, what is y, and what are you trying to do?
>
> [1] http://bit.ly/109oTHs
>
> --
> Lars Buitinck
> Scientific programmer, ILPS
> University of Amsterdam
>
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