Under the hood Mathematica uses libsvm, so I don't think this question is beyond the pale.

I need to export an svm I trained with Classify to the standard SVM Format (which is readable by libsvm).

The SVM format obeys the following Backus-Naur Form (see http://www.cs.cornell.edu/People/tj/svm_light/), it looks like this:

<line> ::= <target> " " (<feature> ":" <value>)+
<target> ::= <positive-integer>
<feature> ::= <positive-integer>
<value> ::= <float>

How can I transform the internal representation of Mathematica's Classifiers into this representation?

Notes:

• MATLAB provides libsvmread to import svms.
• In python sklearn.datasets.load_svmlight_file imports svms.
• Libsvm uses the so called "sparse" format where zero values do not need to be stored.

Under the hood Mathematica uses libsvm, so I don't think this question is beyond the pale.

I need to export an svm I trained with Classify to the standard SVM Format (which is readable by libsvm).

The SVM format obeys the following Backus-Naur Form (see http://www.cs.cornell.edu/People/tj/svm_light/), it looks like this:

<line> ::= <target> " " (<feature> ":" <value>)+
<target> ::= <positive-integer>
<feature> ::= <positive-integer>
<value> ::= <float>

How can I transform the internal representation of Mathematica's Classifiers into this representation?

Notes:

• MATLAB provides libsvmread to import svms.
• In python sklearn.datasets.load_svmlight_file imports svms.
• Libsvm uses the so called "sparse" format where zero values do not need to be stored.

I need to export an svm I trained with Classify to the standard SVM Format (which is readable by libsvm).

The SVM format obeys the following Backus-Naur Form (see http://www.cs.cornell.edu/People/tj/svm_light/), it looks like this:

<line> ::= <target> " " (<feature> ":" <value>)+
<target> ::= <positive-integer>
<feature> ::= <positive-integer>
<value> ::= <float>

How can I transform the internal representation of Mathematica's Classifiers into this representation?

Notes:

• MATLAB provides libsvmread to import svms.
• In python sklearn.datasets.load_svmlight_file imports svms.
• Libsvm uses the so called "sparse" format where zero values do not need to be stored.

Under the hood Mathematica uses libsvm, so I don't think this question is beyond the pale.

I need to export an svm I trained with Classify to the standard SVM Format (which is readable by libsvm).

The SVM format obeys the following Backus-Naur Form (see http://www.cs.cornell.edu/People/tj/svm_light/), it looks like this:

<line> ::= <target> " " (<feature> ":" <value>)+
<target> ::= <positive-integer>
<feature> ::= <positive-integer>
<value> ::= <float>

How can I transform the internal representation of Mathematica's Classifiers into this representation?

Notes:

• MATLAB provides libsvmread to import svms.
• In python sklearn.datasets.load_svmlight_file imports svms.
• Libsvm uses the so called "sparse" format where zero values do not need to be stored.