📄 learnparam.html
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public double <A HREF="../src-html/jnisvmlight/LearnParam.html#line.89"><B>opt_precision</B></A></PRE>
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<DD>Precision of solver, set to e.g. 1e-21 if you get convergence problems.
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<A NAME="predfile"><!-- --></A><H3>
predfile</H3>
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public java.lang.String <A HREF="../src-html/jnisvmlight/LearnParam.html#line.92"><B>predfile</B></A></PRE>
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<DD>File for predicitions on unlabeled examples in transduction.
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<A NAME="remove_inconsistent"><!-- --></A><H3>
remove_inconsistent</H3>
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public long <A HREF="../src-html/jnisvmlight/LearnParam.html#line.95"><B>remove_inconsistent</B></A></PRE>
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<DD>Exclude examples with alpha at C and retrain.
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<A NAME="rho"><!-- --></A><H3>
rho</H3>
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public double <A HREF="../src-html/jnisvmlight/LearnParam.html#line.98"><B>rho</B></A></PRE>
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<DD>Parameter in xi/alpha-estimates and for pruning leave-one-out range [1..2].
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<A NAME="sharedslack"><!-- --></A><H3>
sharedslack</H3>
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public long <A HREF="../src-html/jnisvmlight/LearnParam.html#line.105"><B>sharedslack</B></A></PRE>
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<DD>If nonzero, it will use the shared slack variable mode. In svm_learn_optimization it requires that the slack-id is set for every training example.
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<A NAME="skip_final_opt_check"><!-- --></A><H3>
skip_final_opt_check</H3>
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public long <A HREF="../src-html/jnisvmlight/LearnParam.html#line.111"><B>skip_final_opt_check</B></A></PRE>
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<DD>Do not check KT-Conditions at the end of optimization for examples removed by shrinking. WARNING: This might lead to sub-optimal solutions!
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<A NAME="svm_c"><!-- --></A><H3>
svm_c</H3>
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public double <A HREF="../src-html/jnisvmlight/LearnParam.html#line.114"><B>svm_c</B></A></PRE>
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<DD>Upper bound C on alphas.
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<A NAME="svm_c_factor"><!-- --></A><H3>
svm_c_factor</H3>
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public double <A HREF="../src-html/jnisvmlight/LearnParam.html#line.117"><B>svm_c_factor</B></A></PRE>
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<DD>Increase C by this factor every step.
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<A NAME="svm_c_steps"><!-- --></A><H3>
svm_c_steps</H3>
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public long <A HREF="../src-html/jnisvmlight/LearnParam.html#line.120"><B>svm_c_steps</B></A></PRE>
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<DD>Do so many steps for finding optimal C.
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<A NAME="svm_cost"><!-- --></A><H3>
svm_cost</H3>
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public double <A HREF="../src-html/jnisvmlight/LearnParam.html#line.123"><B>svm_cost</B></A></PRE>
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<DD>Individual upper bounds for each var.
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<A NAME="svm_costratio"><!-- --></A><H3>
svm_costratio</H3>
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public double <A HREF="../src-html/jnisvmlight/LearnParam.html#line.126"><B>svm_costratio</B></A></PRE>
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<DD>Factor to multiply C for positive examples.
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<A NAME="svm_costratio_unlab"><!-- --></A><H3>
svm_costratio_unlab</H3>
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public double <A HREF="../src-html/jnisvmlight/LearnParam.html#line.128"><B>svm_costratio_unlab</B></A></PRE>
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<A NAME="svm_iter_to_shrink"><!-- --></A><H3>
svm_iter_to_shrink</H3>
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public long <A HREF="../src-html/jnisvmlight/LearnParam.html#line.133"><B>svm_iter_to_shrink</B></A></PRE>
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<DD>Iterations h after which an example can be removed by shrinking.
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<A NAME="svm_maxqpsize"><!-- --></A><H3>
svm_maxqpsize</H3>
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public long <A HREF="../src-html/jnisvmlight/LearnParam.html#line.136"><B>svm_maxqpsize</B></A></PRE>
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<DD>Size q of working set.
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<A NAME="svm_newvarsinqp"><!-- --></A><H3>
svm_newvarsinqp</H3>
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public long <A HREF="../src-html/jnisvmlight/LearnParam.html#line.139"><B>svm_newvarsinqp</B></A></PRE>
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<DD>New variables to enter the working set in each iteration.
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<A NAME="svm_unlabbound"><!-- --></A><H3>
svm_unlabbound</H3>
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public double <A HREF="../src-html/jnisvmlight/LearnParam.html#line.143"><B>svm_unlabbound</B></A></PRE>
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<A NAME="totwords"><!-- --></A><H3>
totwords</H3>
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public long <A HREF="../src-html/jnisvmlight/LearnParam.html#line.146"><B>totwords</B></A></PRE>
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<DD>Total amount of features.
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<A NAME="transduction_posratio"><!-- --></A><H3>
transduction_posratio</H3>
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public double <A HREF="../src-html/jnisvmlight/LearnParam.html#line.149"><B>transduction_posratio</B></A></PRE>
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<DD>Fraction of unlabeled examples to be classified as positives.
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<A NAME="type"><!-- --></A><H3>
type</H3>
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public long <A HREF="../src-html/jnisvmlight/LearnParam.html#line.152"><B>type</B></A></PRE>
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<DD>Selects between CLASSIFICATION, REGRESSION, RANKING, or OPTIMIZATION mode.
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<A NAME="verbosity"><!-- --></A><H3>
verbosity</H3>
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public int <A HREF="../src-html/jnisvmlight/LearnParam.html#line.155"><B>verbosity</B></A></PRE>
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<DD>The level of SVM-light debugging infos.
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<A NAME="xa_depth"><!-- --></A><H3>
xa_depth</H3>
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public long <A HREF="../src-html/jnisvmlight/LearnParam.html#line.161"><B>xa_depth</B></A></PRE>
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<DD>Parameter in xi/alpha-estimates upper bounding the number of SV the current alpha_t is distributed over.
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LearnParam</H3>
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public <A HREF="../src-html/jnisvmlight/LearnParam.html#line.164"><B>LearnParam</B></A>()</PRE>
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<DD>Initializes the learning parameters with the default SVM-light values.
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