C++ GMatrix::deleteColumns方法代码示例

void GRecommenderLib::precisionRecall(GArgReader& args)
{
	// Parse options
	unsigned int seed = getpid() * (unsigned int)time(NULL);
	bool ideal = false;
	while(args.next_is_flag())
	{
		if(args.if_pop("-seed"))
			seed = args.pop_uint();
		else if(args.if_pop("-ideal"))
			ideal = true;
		else
			throw Ex("Invalid option: ", args.peek());
	}

	// Load the data
	if(args.size() < 1)
		throw Ex("No dataset specified.");
	GMatrix data;
	loadData(data, args.pop_string());

	// Instantiate the recommender
	GCollaborativeFilter* pModel = InstantiateAlgorithm(args);
	std::unique_ptr<GCollaborativeFilter> hModel(pModel);
	if(args.size() > 0)
		throw Ex("Superfluous argument: ", args.peek());
	pModel->rand().setSeed(seed);

	// Generate precision-recall data
	GMatrix* pResults = pModel->precisionRecall(data, ideal);
	std::unique_ptr<GMatrix> hResults(pResults);
	pResults->deleteColumns(2, 1); // we don't need the false-positive rate column
	pResults->print(cout);
}

void GRecommenderLib::fillMissingValues(GArgReader& args)
{
	unsigned int seed = getpid() * (unsigned int)time(NULL);
	bool normalize = true;
	while(args.next_is_flag())
	{
		if(args.if_pop("-seed"))
			seed = args.pop_uint();
		else if(args.if_pop("-nonormalize"))
			normalize = false;
		else
			throw Ex("Invalid option: ", args.peek());
	}

	// Load the data and the filter
	GMatrix dataOrig;
	dataOrig.loadArff(args.pop_string());

	// Parse params
	vector<size_t> ignore;
	while(args.next_is_flag())
	{
		if(args.if_pop("-ignore"))
			parseAttributeList(ignore, args, dataOrig.cols());
		else
			throw Ex("Invalid option: ", args.peek());
	}

	// Throw out the ignored attributes
	std::sort(ignore.begin(), ignore.end());
	for(size_t i = ignore.size() - 1; i < ignore.size(); i--)
		dataOrig.deleteColumns(ignore[i], 1);

	GRelation* pOrigRel = dataOrig.relation().clone();
	std::unique_ptr<GRelation> hOrigRel(pOrigRel);
	GCollaborativeFilter* pModel = InstantiateAlgorithm(args);
	std::unique_ptr<GCollaborativeFilter> hModel(pModel);
	if(args.size() > 0)
		throw Ex("Superfluous argument: ", args.peek());
	pModel->rand().setSeed(seed);

	// Convert to all normalized real values
	GNominalToCat* pNtc = new GNominalToCat();
	GIncrementalTransform* pFilter = pNtc;
	std::unique_ptr<GIncrementalTransformChainer> hChainer;
	if(normalize)
	{
		GIncrementalTransformChainer* pChainer = new GIncrementalTransformChainer(new GNormalize(), pNtc);
		hChainer.reset(pChainer);
		pFilter = pChainer;
	}
	pNtc->preserveUnknowns();
	pFilter->train(dataOrig);
	GMatrix* pData = pFilter->transformBatch(dataOrig);
	std::unique_ptr<GMatrix> hData(pData);

	// Convert to 3-column form
	GMatrix* pMatrix = new GMatrix(0, 3);
	std::unique_ptr<GMatrix> hMatrix(pMatrix);
	size_t dims = pData->cols();
	for(size_t i = 0; i < pData->rows(); i++)
	{
		GVec& row = pData->row(i);
		for(size_t j = 0; j < dims; j++)
		{
			if(row[j] != UNKNOWN_REAL_VALUE)
			{
				GVec& vec = pMatrix->newRow();
				vec[0] = (double)i;
				vec[1] = (double)j;
				vec[2] = row[j];
			}
		}
	}

	// Train the collaborative filter
	pModel->train(*pMatrix);
	hMatrix.release();
	pMatrix = NULL;

	// Predict values for missing elements
	for(size_t i = 0; i < pData->rows(); i++)
	{
		GVec& row = pData->row(i);
		for(size_t j = 0; j < dims; j++)
		{
			if(row[j] == UNKNOWN_REAL_VALUE)
				row[j] = pModel->predict(i, j);
			GAssert(row[j] != UNKNOWN_REAL_VALUE);
		}
	}

	// Convert the data back to its original form
	GMatrix* pOut = pFilter->untransformBatch(*pData);
	pOut->setRelation(hOrigRel.release());
	pOut->print(cout);
}

///Return a pointer to newly allocated data read from the command line
///represented by args.
///
///The returned matrix is allocated by new and it is the caller's
///responsibility to deallocate it. The suggested manner is to use a
///Holder<GMatrix*>
///
///In the returned matrix, all of the attributes designated as labels
///have been moved to the end and ignored attributes have been
///removed. The original indices of all the attributes are returned in
///originalIndices.
///
///\param args the command-line arguments
///
///\param pLabelDims (out parameter) the index of the first attribute
///which is designated a label.
///
///\param originalIndices the vector in which to place the original
///indices.  originalIndices[i] is the index in the original data file
///of the attribute currently at index i.
void loadDataWithSwitches(GMatrix& data, GArgReader& args, size_t& pLabelDims,
			      std::vector<size_t>& originalIndices)
{
	// Load the dataset by extension
	const char* szFilename = args.pop_string();
	PathData pd;
	GFile::parsePath(szFilename, &pd);
	if(_stricmp(szFilename + pd.extStart, ".arff") == 0)
		data.loadArff(szFilename);
	else if(_stricmp(szFilename + pd.extStart, ".csv") == 0)
	{
		GCSVParser parser;
		parser.parse(data, szFilename);
		cerr << "\nParsing Report:\n";
		for(size_t i = 0; i < data.cols(); i++)
			cerr << to_str(i) << ") " << parser.report(i) << "\n";
	}
	else if(_stricmp(szFilename + pd.extStart, ".dat") == 0)
	{
		GCSVParser parser;
		parser.setSeparator('\0');
		parser.parse(data, szFilename);
		cerr << "\nParsing Report:\n";
		for(size_t i = 0; i < data.cols(); i++)
			cerr << to_str(i) << ") " << parser.report(i) << "\n";
	}
	else
		throw Ex("Unsupported file format: ", szFilename + pd.extStart);

	//Make the initial list of original indices
	originalIndices.resize(data.cols());
	for(std::size_t i = 0; i < originalIndices.size(); ++i){
	  originalIndices.at(i) = i;
	}

	// Parse params
	vector<size_t> ignore;
	vector<size_t> labels;
	while(args.next_is_flag())
	{
		if(args.if_pop("-labels"))
			parseAttributeList(labels, args, data.cols());
		else if(args.if_pop("-ignore"))
			parseAttributeList(ignore, args, data.cols());
		else
			break;
	}

	// Throw out the ignored attributes
	std::sort(ignore.begin(), ignore.end());
	for(size_t i = ignore.size() - 1; i < ignore.size(); i--)
	{
		data.deleteColumns(ignore[i], 1);
		originalIndices.erase(originalIndices.begin()+ignore[i]);
		for(size_t j = 0; j < labels.size(); j++)
		{
			if(labels[j] >= ignore[i])
			{
				if(labels[j] == ignore[i])
					throw Ex("Attribute ", to_str(labels[j]), " is both ignored and used as a label");
				labels[j]--;
			}
		}
	}

	// Swap label columns to the end
	pLabelDims = std::max((size_t)1, labels.size());
	for(size_t i = 0; i < labels.size(); i++)
	{
		size_t src = labels[i];
		size_t dst = data.cols() - pLabelDims + i;
		if(src != dst)
		{
			data.swapColumns(src, dst);
			std::swap(originalIndices.at(src),
				  originalIndices.at(dst));
			for(size_t j = i + 1; j < labels.size(); j++)
			{
				if(labels[j] == dst)
				{
//.........这里部分代码省略.........