Thanks for your response Andy.
Is there another application that might help me plot this information on a
graph? Really what I am looking for is perhaps to assign a numerical
representation for each sample based off of the 18 attributes and then plot
that numerical representation on a graph to see which samples are similar
to other samples. My math is not strong at all so I am not even sure if
that is possible or not.
On Wed, Nov 19, 2014 at 12:20 PM, Andy <[email protected]> wrote:
> Hi.
>
> The example is meant to illustrate the prediction boundaries on a 2d
> example.
> You can not plot the decision boundaries like that for higher dimensions.
>
> Just predicting should work fine, though.
>
> Hth,
> Andy
>
>
>
> On 11/19/2014 11:56 AM, John Doe wrote:
>
> I have just started using scikit and I have been following the example
> code at
> http://scikit-learn.org/stable/auto_examples/neighbors/plot_classification.html
>
>
> I am having some trouble with my data, here is the code that I have been
> using to import my data from csv files that I dump out of a database.
>
>
> query_csv_file = 'query_result.csv'
>
> X = np.loadtxt(fname = query_csv_file, delimiter = ',', skiprows = 1)
>
> id_csv_file = 'query_id.csv'
>
> y = np.loadtxt(fname = id_csv_file, delimiter = ‘,', skiprows = 1)
>
>
> query_result.csv looks like the following:
>
>
> attr1,attr2,attr3,attr4,attr5,attr6,attr7,attr8,attr9,attr10,attr11,attr12,attr13,attr14,attr15,attr16,attr17,attr18
>
> 0,797.3700774,0,330.8733288
> ,155.4552568,0,6177.289831,0,355.3611942,82.92122107,0,49.93354722,1592.292597,435.3831843,721.4373622,73.07706747,194.5707382,0
>
>
> query_id.csv looks like the following:
>
> id
>
> 1
>
>
> If I try to run the code in the example using this data I get the
> following error:
>
> ValueError: Incompatible dimension for X and Y matrices: X.shape[1] == 2
> while Y.shape[1] == 18
>
>
> If I add the following line of code it works but then it is not using
> all 18 attributes:
>
> X = X[:, :2]
>
>
> Any help or guidance would be appreciated! Thanks in advance!
>
>
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