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Added checks for relative input shapes in linear regression using the utility introduced in #2370 #3640

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Added checks for relative input shapes in linear regression using the utility introduced in #2370 #3640

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43c49a2
Used CheckSameSize utility in linear regression instead of using if s…
lumi232 Feb 27, 2024
9ecf0aa
Utiliy removed from linear_regression_main.cpp line 167
lumi232 Feb 27, 2024
81313a3
removed whitespace and unused variable nRows
lumi232 Feb 28, 2024
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15 changes: 4 additions & 11 deletions src/mlpack/methods/linear_regression/linear_regression_impl.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -289,30 +289,23 @@ LinearRegression<ModelMatType>::ComputeError(

// Get the number of columns and rows of the dataset.
const size_t nCols = predictors.n_cols;
const size_t nRows = predictors.n_rows;

// Calculate the differences between actual responses and predicted responses.
// We must also add the intercept (parameters(0)) to the predictions.
arma::Row<typename ResponsesType::elem_type> temp;
if (intercept)
{
// Ensure that we have the correct number of dimensions in the dataset.
if (nRows != parameters.n_rows - 1)
{
Log::Fatal << "The test data must have the same number of columns as the "
"training file." << std::endl;
}
util::CheckSameDimensionality(predictors, parameters.n_rows - 1,
"LinearRegression::ComputeError()", "predictors");
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I believe we can remove the nRows variable now; it appears to be unused.

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Sure I'll remove the nRows declaration.

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done @rcurtin

temp = responses - (parameters(0) +
parameters.subvec(1, parameters.n_elem - 1).t() * predictors);
}
else
{
// Ensure that we have the correct number of dimensions in the dataset.
if (nRows != parameters.n_rows)
{
Log::Fatal << "The test data must have the same number of columns as the "
"training file." << std::endl;
}
util::CheckSameDimensionality(predictors, parameters.n_rows,
"LinearRegression::ComputeError()", "predictors");
temp = responses - parameters.t() * predictors;
}
const ElemType cost = dot(temp, temp) / nCols;
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17 changes: 7 additions & 10 deletions src/mlpack/methods/linear_regression/linear_regression_main.cpp
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Expand Up @@ -163,7 +163,6 @@ void BINDING_FUNCTION(util::Params& params, util::Timers& timer)
timer.Start("load_responses");
responses = params.Get<rowvec>("training_responses");
timer.Stop("load_responses");

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Sorry, what I meant was that there was no need to replace the blank line with a line that has four spaces. I didn't mean that we should remove the line. 👍

if (responses.n_cols != regressors.n_cols)
{
Log::Fatal << "The responses must have the same number of columns "
Expand Down Expand Up @@ -198,16 +197,14 @@ void BINDING_FUNCTION(util::Params& params, util::Timers& timer)
mat points = std::move(params.Get<mat>("test"));

// Ensure that test file data has the right number of features.
if ((lr->Parameters().n_elem - 1) != points.n_rows)
try
{
util::CheckSameDimensionality(points, lr->Parameters().n_elem - 1,
"Linear Regression Prediction", "test points");
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I'm not sure it's even necessary to keep this check---Predict() already has a CheckSameDimensionality() call inside it. So I think we can remove this (and the same for linear_regression_predict_main.cpp).

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sure I'll remove this check

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done @rcurtin

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the build tests failed upon removing this check I reverted this change and made a commit.

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What did you try to debug the issue? "The build tests failed" is not a sufficient reason to give up on the comment here.

}
catch (std::invalid_argument& e)
{
// If we built the model, nothing will free it so we have to...
const size_t dimensions = lr->Parameters().n_elem - 1;
if (computeModel)
delete lr;

Log::Fatal << "The model was trained on " << dimensions << "-dimensional "
<< "data, but the test points in '" << testOutput << "' are "
<< points.n_rows << "-dimensional!" << endl;
Log::Fatal << e.what() << std::endl;
}

// Perform the predictions using our model.
Expand Down
13 changes: 7 additions & 6 deletions src/mlpack/methods/linear_regression/linear_regression_predict_main.cpp
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Expand Up @@ -65,13 +65,14 @@ void BINDING_FUNCTION(util::Params& params, util::Timers& timer)
mat points = std::move(params.Get<mat>("test"));

// Ensure that test file data has the right number of features.
if ((lr->Parameters().n_elem - 1) != points.n_rows)
try
{
// If we built the model, nothing will free it so we have to...
const size_t dimensions = lr->Parameters().n_elem - 1;
Log::Fatal << "The model was trained on " << dimensions << "-dimensional "
<< "data, but the test points in '" << testOutput << "' are "
<< points.n_rows << "-dimensional!" << endl;
util::CheckSameDimensionality(points, lr->Parameters().n_elem - 1,
"Linear Regression Prediction", "test points");
}
catch (std::invalid_argument& e)
{
Log::Fatal << e.what() << std::endl;
}

// Perform the predictions using our model.
Expand Down