Example #1
0
void MDDAGClassifier::run(const string& dataFileName, const string& shypFileName,
                          int numIterations, const string& outResFileName, int numRanksEnclosed)
{
    InputData* pData = loadInputData(dataFileName, shypFileName);

    if (_verbose > 0)
        cout << "Loading strong hypothesis..." << flush;

    // The class that loads the weak hypotheses
    UnSerialization us;

    // Where to put the weak hypotheses
    vector<BaseLearner*> weakHypotheses;

    // loads them
    us.loadHypotheses(shypFileName, weakHypotheses, pData);

    // where the results go
    vector< ExampleResults* > results;

    if (_verbose > 0)
        cout << "Classifying..." << flush;

    // get the results
    computeResults( pData, weakHypotheses, results, numIterations );

    const int numClasses = pData->getNumClasses();

    if (_verbose > 0)
    {
        // well.. if verbose = 0 no results are displayed! :)
        cout << "Done!" << endl;

        vector< vector<float> > rankedError(numRanksEnclosed);

        // Get the per-class error for the numRanksEnclosed-th ranks
        for (int i = 0; i < numRanksEnclosed; ++i)
            getClassError( pData, results, rankedError[i], i );

        // output it
        cout << endl;
        cout << "Error Summary" << endl;
        cout << "=============" << endl;

        for ( int l = 0; l < numClasses; ++l )
        {
            // first rank (winner): rankedError[0]
            cout << "Class '" << pData->getClassMap().getNameFromIdx(l) << "': "
                 << setprecision(4) << rankedError[0][l] * 100 << "%";

            // output the others on its side
            if (numRanksEnclosed > 1 && _verbose > 1)
            {
                cout << " (";
                for (int i = 1; i < numRanksEnclosed; ++i)
                    cout << " " << i+1 << ":[" << setprecision(4) << rankedError[i][l] * 100 << "%]";
                cout << " )";
            }

            cout << endl;
        }

        // the overall error
        cout << "\n--> Overall Error: "
             << setprecision(4) << getOverallError(pData, results, 0) * 100 << "%";

        // output the others on its side
        if (numRanksEnclosed > 1 && _verbose > 1)
        {
            cout << " (";
            for (int i = 1; i < numRanksEnclosed; ++i)
                cout << " " << i+1 << ":[" << setprecision(4) << getOverallError(pData, results, i) * 100 << "%]";
            cout << " )";
        }

        cout << endl;

    } // verbose


    // If asked output the results
    if ( !outResFileName.empty() )
    {
        const int numExamples = pData->getNumExamples();
        ofstream outRes(outResFileName.c_str());

        outRes << "Instance" << '\t' << "Forecast" << '\t' << "Labels" << '\n';

        string exampleName;

        for (int i = 0; i < numExamples; ++i)
        {
            // output the name if it exists, otherwise the number
            // of the example
            exampleName = pData->getExampleName(i);
            if ( exampleName.empty() )
                outRes << i << '\t';
            else
                outRes << exampleName << '\t';

            // output the predicted class
            outRes << pData->getClassMap().getNameFromIdx( results[i]->getWinner().first ) << '\t';

            outRes << '|';

            vector<Label>& labels = pData->getLabels(i);
            for (vector<Label>::iterator lIt=labels.begin(); lIt != labels.end(); ++lIt) {
                if (lIt->y>0)
                {
                    outRes << ' ' << pData->getClassMap().getNameFromIdx(lIt->idx);
                }
            }

            outRes << endl;
        }

        if (_verbose > 0)
            cout << "\nPredictions written on file <" << outResFileName << ">!" << endl;

    }


    // delete the input data file
    if (pData)
        delete pData;

    vector<ExampleResults*>::iterator it;
    for (it = results.begin(); it != results.end(); ++it)
        delete (*it);
}
Example #2
0
void MDDAGClassifier::saveCalibratedPosteriors(const string& dataFileName, const string& shypFileName,
        const string& outFileName, int numIterations)
{
    InputData* pData = loadInputData(dataFileName, shypFileName);

    if (_verbose > 0)
        cout << "Loading strong hypothesis..." << flush;

    // The class that loads the weak hypotheses
    UnSerialization us;

    // Where to put the weak hypotheses
    vector<BaseLearner*> weakHypotheses;

    // loads them
    us.loadHypotheses(shypFileName, weakHypotheses, pData);

    // where the results go
    vector< ExampleResults* > results;

    if (_verbose > 0)
        cout << "Classifying..." << flush;

    // get the results
    computeResults( pData, weakHypotheses, results, numIterations );

    const int numClasses = pData->getNumClasses();
    const int numExamples = pData->getNumExamples();

    ofstream outFile(outFileName.c_str());
    string exampleName;

    if (_verbose > 0)
        cout << "Output posteriors..." << flush;

    for (int i = 0; i < numExamples; ++i)
    {
        // output the name if it exists, otherwise the number
        // of the example
        exampleName = pData->getExampleName(i);
        if ( !exampleName.empty() )
            outFile << exampleName << ',';

        // output the posteriors
        outFile << results[i]->getVotesVector()[0];
        for (int l = 1; l < numClasses; ++l)
            outFile << ',' << results[i]->getVotesVector()[l];
        outFile << '\n';
    }

    if (_verbose > 0)
        cout << "Done!" << endl;

    if (_verbose > 1)
    {
        cout << "\nClass order (You can change it in the header of the data file):" << endl;
        for (int l = 0; l < numClasses; ++l)
            cout << "- " << pData->getClassMap().getNameFromIdx(l) << endl;
    }

    // delete the input data file
    if (pData)
        delete pData;

    vector<ExampleResults*>::iterator it;
    for (it = results.begin(); it != results.end(); ++it)
        delete (*it);
}