parameter change in perceptron.cpp
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@@ -47,10 +47,18 @@ PROGRAM_INFO("Perceptron",
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" parameter), or both those things at once. In addition, this program "
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"allows classification on a test dataset (via the " +
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PRINT_PARAM_STRING("test") + " parameter) and the classification results "
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"on the test set may be saved with the " + PRINT_PARAM_STRING("output") +
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"on the test set may be saved with the " + PRINT_PARAM_STRING("predictions") +
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"output parameter. The perceptron model may be saved with the " +
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PRINT_PARAM_STRING("output_model") + " output parameter."
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"\n\n"
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"Note : The following parameters are deprecated and "
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"will be removed in mlpack 4: " + PRINT_PARAM_STRING("output") +
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", " + PRINT_PARAM_STRING("output_probabilities") +
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"\nUse " + PRINT_PARAM_STRING("predictions") + " instead of " +
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PRINT_PARAM_STRING("output") + "\nUse " +
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PRINT_PARAM_STRING("probabilities") + " instead of " +
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PRINT_PARAM_STRING("output_probabilities") +
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"\n\n"
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"The training data given with the " + PRINT_PARAM_STRING("training") +
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" option may have class labels as its last dimension (so, if the training "
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"data is in CSV format, labels should be the last column). Alternately, "
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@@ -126,8 +134,14 @@ PARAM_MODEL_OUT(PerceptronModel, "output_model", "Output for trained perceptron"
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// Testing/classification parameters.
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PARAM_MATRIX_IN("test", "A matrix containing the test set.", "T");
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/*
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* The PARAM_UROW_OUT("output") is depracated and
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* can be removed in mlpack4.0.0.
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*/
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PARAM_UROW_OUT("output", "The matrix in which the predicted labels for the"
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" test set will be written.", "o");
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PARAM_UROW_OUT("predictions", "The matrix in which the predicted labels for the"
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" test set will be written.", "P");
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static void mlpackMain()
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{
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@@ -141,7 +155,9 @@ static void mlpackMain()
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// should issue a warning.
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RequireAtLeastOnePassed({ "output_model", "output" }, false,
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"no output will be saved");
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// "output" can be removed in mlpack 4
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ReportIgnoredParam({{ "test", false }}, "output");
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ReportIgnoredParam({{ "test", false }}, "predictions");
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// Check parameter validity.
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RequireParamValue<int>("max_iterations", [](int x) { return x >= 0; },
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@@ -297,6 +313,8 @@ static void mlpackMain()
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// Save the predicted labels.
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if (CLI::HasParam("output"))
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CLI::GetParam<arma::Row<size_t>>("output") = std::move(results);
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if (CLI::HasParam("predictions"))
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CLI::GetParam<arma::Row<size_t>>("predictions") = std::move(results);
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}
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// Lastly, save the output model.
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