AI-MaxEntropy

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AI-MaxEntropy.xs  view on Meta::CPAN

	SV*     self
    PREINIT:
	dTRACE("_neg_log_likelihood");
        /* fetch the pre-cached samples and f_map */
	SV* _c = *hvref_fetch(self, "_c");
	struct samples_t* samples =
	    INT2PTR(struct samples_t*, SvIV(*hvref_fetch(_c, "samples")));
	struct f_map_t* f_map =
	    INT2PTR(struct f_map_t*, SvIV(*hvref_fetch(_c, "f_map")));
	int** lambda_idx = f_map->lambda_idx;
	/* fetch other useful data */
	SV* smoother = *hvref_fetch(self, "smoother");
        int x_num = SvIV(*hvref_fetch(self, "x_num"));
	int y_num = SvIV(*hvref_fetch(self, "y_num"));
	int f_num = SvIV(*hvref_fetch(self, "f_num"));
	/* intermediate variables */
	AV* av_d_log_lh;
	char* smoother_type;
	int i, j, x, y, lambda_i;
        double log_lh, sum_exp_lambda_f, sigma, fxy;
	double* lambda_f = (double*)malloc(sizeof(double) * y_num);

README  view on Meta::CPAN

      $me->see(['rough', 'big'] => 'pomelo');

      # the order of active features is not concerned, too
      $me->see(['big', 'rough'] => 'pomelo');

      # ...

      # and, let it learn
      my $model = $me->learn;

      # then, we can make predictions on unseen data

      # ask what a red thing is most likely to be
      print $model->predict(['red'])."\n";
      # the answer is apple, because all red things the learner have ever seen
      # are apples
  
      # ask what a smooth thing is most likely to be
      print $model->predict(['smooth'])."\n";
      # the answer is banana, because the learner have seen more smooth bananas
      # (weighted 3) than smooth apples (weighted 2)

lib/AI/MaxEntropy.pm  view on Meta::CPAN

  $me->see(['rough', 'big'] => 'pomelo');

  # the order of active features is not concerned, too
  $me->see(['big', 'rough'] => 'pomelo');

  # ...

  # and, let it learn
  my $model = $me->learn;

  # then, we can make predictions on unseen data

  # ask what a red thing is most likely to be
  print $model->predict(['red'])."\n";
  # the answer is apple, because all red things the learner have ever seen
  # are apples
  
  # ask what a smooth thing is most likely to be
  print $model->predict(['smooth'])."\n";
  # the answer is banana, because the learner have seen more smooth bananas
  # (weighted 3) than smooth apples (weighted 2)

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