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      "page": "classification_fer.factor",
      "title": "False Omission Rate",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "fer.factor"
      ]
    },
    {
      "page": "classification_fmi",
      "title": "Fowlkes Mallows Index",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "fmi",
        "weighted.fmi"
      ]
    },
    {
      "page": "classification_fmi.cmatrix",
      "title": "Fowlkes Mallows Index",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "fmi.cmatrix"
      ]
    },
    {
      "page": "classification_fmi.factor",
      "title": "Fowlkes Mallows Index",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "fmi.factor"
      ]
    },
    {
      "page": "classification_fpr",
      "title": "False Positive Rate",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "fallout",
        "fpr",
        "weighted.fallout",
        "weighted.fpr"
      ]
    },
    {
      "page": "classification_fpr.cmatrix",
      "title": "False Positive Rate",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "fpr.cmatrix"
      ]
    },
    {
      "page": "classification_fpr.factor",
      "title": "False Positive Rate",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "fpr.factor"
      ]
    },
    {
      "page": "regression_gmse",
      "title": "Geometric Mean Squared Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "gmse",
        "weighted.gmse"
      ]
    },
    {
      "page": "regression_gmse.numeric",
      "title": "Geometric Mean Squared Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "gmse.numeric"
      ]
    },
    {
      "page": "classification_hammingloss",
      "title": "Hamming Loss",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "hammingloss",
        "weighted.hammingloss"
      ]
    },
    {
      "page": "classification_hammingloss.cmatrix",
      "title": "Hamming Loss",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "hammingloss.cmatrix"
      ]
    },
    {
      "page": "classification_hammingloss.factor",
      "title": "Hamming Loss",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "hammingloss.factor"
      ]
    },
    {
      "page": "regression_huberloss",
      "title": "Huber Loss",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "huberloss",
        "weighted.huberloss"
      ]
    },
    {
      "page": "regression_huberloss.numeric",
      "title": "Huber Loss",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "huberloss.numeric"
      ]
    },
    {
      "page": "classification_jaccard",
      "title": "Jaccard Index",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "csi",
        "jaccard",
        "tscore",
        "weighted.csi",
        "weighted.jaccard",
        "weighted.tscore"
      ]
    },
    {
      "page": "classification_jaccard.cmatrix",
      "title": "Jaccard Index",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "jaccard.cmatrix"
      ]
    },
    {
      "page": "classification_jaccard.factor",
      "title": "Jaccard Index",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "jaccard.factor"
      ]
    },
    {
      "page": "classification_logloss",
      "title": "Logarithmic Loss",
      "concept": [
        "Classification",
        "Entropy",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "logloss",
        "weighted.logloss"
      ]
    },
    {
      "page": "classification_logloss.factor",
      "title": "Logarithmic Loss",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "logloss.factor"
      ]
    },
    {
      "page": "classification_logloss.integer",
      "title": "Logarithmic Loss",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "logloss.integer"
      ]
    },
    {
      "page": "regression_maape",
      "title": "Mean Arctangent Absolute Percentage Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "maape",
        "weighted.maape"
      ]
    },
    {
      "page": "regression_maape.numeric",
      "title": "Mean Arctangent Absolute Percentage Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "maape.numeric"
      ]
    },
    {
      "page": "regression_mae",
      "title": "Mean Absolute Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "mae",
        "weighted.mae"
      ]
    },
    {
      "page": "regression_mae.numeric",
      "title": "Mean Absolute Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "mae.numeric"
      ]
    },
    {
      "page": "regression_mape",
      "title": "Mean Absolute Percentage Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "mape",
        "weighted.mape"
      ]
    },
    {
      "page": "regression_mape.numeric",
      "title": "Mean Absolute Percentage Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "mape.numeric"
      ]
    },
    {
      "page": "classification_mcc",
      "title": "Matthews Correlation Coefficient",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "mcc",
        "phi",
        "weighted.mcc",
        "weighted.phi"
      ]
    },
    {
      "page": "classification_mcc.cmatrix",
      "title": "Matthews Correlation Coefficient",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "mcc.cmatrix"
      ]
    },
    {
      "page": "classification_mcc.factor",
      "title": "Matthews Correlation Coefficient",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "mcc.factor"
      ]
    },
    {
      "page": "regression_mpe",
      "title": "Mean Percentage Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "mpe",
        "weighted.mpe"
      ]
    },
    {
      "page": "regression_mpe.numeric",
      "title": "Mean Percentage Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "mpe.numeric"
      ]
    },
    {
      "page": "regression_mse",
      "title": "Mean Squared Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "mse",
        "weighted.mse"
      ]
    },
    {
      "page": "regression_mse.numeric",
      "title": "Mean Squared Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "mse.numeric"
      ]
    },
    {
      "page": "classification_nlr",
      "title": "Negative Likelihood Ratio",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "nlr",
        "weighted.nlr"
      ]
    },
    {
      "page": "classification_nlr.cmatrix",
      "title": "Negative Likelihood Ratio",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "nlr.cmatrix"
      ]
    },
    {
      "page": "classification_nlr.factor",
      "title": "Negative Likelihood Ratio",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "nlr.factor"
      ]
    },
    {
      "page": "classification_npv",
      "title": "Negative Predictive Value",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "npv",
        "weighted.npv"
      ]
    },
    {
      "page": "classification_npv.cmatrix",
      "title": "Negative Predictive Value",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "npv.cmatrix"
      ]
    },
    {
      "page": "classification_npv.factor",
      "title": "Negative Predictive Value",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "npv.factor"
      ]
    },
    {
      "page": "data_obesity",
      "title": "Obesity levels dataset",
      "topics": [
        "obesity"
      ]
    },
    {
      "page": "utils_OpenMP",
      "title": "Control OpenMP",
      "topics": [
        "OpenMP",
        "openmp.off",
        "openmp.on",
        "openmp.threads"
      ]
    },
    {
      "page": "regression_pinball",
      "title": "Pinball Loss",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "pinball",
        "weighted.pinball"
      ]
    },
    {
      "page": "regression_pinball.numeric",
      "title": "Pinball Loss",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "pinball.numeric"
      ]
    },
    {
      "page": "classification_plr",
      "title": "Positive Likelihood Ratio",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "plr",
        "weighted.dor",
        "weighted.plr"
      ]
    },
    {
      "page": "classification_plr.cmatrix",
      "title": "Positive Likelihood Ratio",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "plr.cmatrix"
      ]
    },
    {
      "page": "classification_plr.factor",
      "title": "Positive Likelihood Ratio",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "plr.factor"
      ]
    },
    {
      "page": "classification_pr.curve",
      "title": "Precision Recall Curve",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "pr.curve",
        "weighted.pr.curve"
      ]
    },
    {
      "page": "classification_pr.curve.factor",
      "title": "Precision Recall Curve",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "pr.curve.factor"
      ]
    },
    {
      "page": "classification_precision",
      "title": "Precision",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "ppv",
        "precision",
        "weighted.ppv",
        "weighted.precision"
      ]
    },
    {
      "page": "classification_precision.cmatrix",
      "title": "Precision",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "precision.cmatrix"
      ]
    },
    {
      "page": "classification_precision.factor",
      "title": "Precision",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "precision.factor"
      ]
    },
    {
      "page": "utils_preorder",
      "title": "Preorder Matrices",
      "concept": [
        "Utilities"
      ],
      "topics": [
        "preorder"
      ]
    },
    {
      "page": "utils_preorder.matrix",
      "title": "Preorder Matrices",
      "topics": [
        "preorder.matrix"
      ]
    },
    {
      "page": "utils_presort",
      "title": "Presort Matrices",
      "concept": [
        "Utilities"
      ],
      "topics": [
        "presort"
      ]
    },
    {
      "page": "utils_presort.matrix",
      "title": "Presort Matrices",
      "topics": [
        "presort.matrix"
      ]
    },
    {
      "page": "regression_rae",
      "title": "Relative Absolute Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "rae",
        "weighted.rae"
      ]
    },
    {
      "page": "regression_rae.numeric",
      "title": "Relative Absolute Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "rae.numeric"
      ]
    },
    {
      "page": "classification_recall",
      "title": "Recall",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "recall",
        "sensitivity",
        "tpr",
        "weighted.recall",
        "weighted.sensitivity",
        "weighted.tpr"
      ]
    },
    {
      "page": "classification_recall.cmatrix",
      "title": "Recall",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "recall.cmatrix"
      ]
    },
    {
      "page": "classification_recall.factor",
      "title": "Recall",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "recall.factor"
      ]
    },
    {
      "page": "classification_relative.entropy",
      "title": "Relative Entropy",
      "concept": [
        "Classification",
        "Entropy",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "relative.entropy"
      ]
    },
    {
      "page": "classification_relative.entropy.matrix",
      "title": "Relative Entropy",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "relative.entropy.matrix"
      ]
    },
    {
      "page": "regression_rmse",
      "title": "Root Mean Squared Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "rmse",
        "weighted.rmse"
      ]
    },
    {
      "page": "regression_rmse.numeric",
      "title": "Root Mean Squared Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "rmse.numeric"
      ]
    },
    {
      "page": "regression_rmsle",
      "title": "Root Mean Squared Logarithmic Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "rmsle",
        "weighted.rmsle"
      ]
    },
    {
      "page": "regression_rmsle.numeric",
      "title": "Root Mean Squared Logarithmic Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "rmsle.numeric"
      ]
    },
    {
      "page": "classification_roc.curve",
      "title": "Reciever Operator Characteristics",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "roc.curve",
        "weighted.roc.curve"
      ]
    },
    {
      "page": "classification_roc.curve.factor",
      "title": "Reciever Operator Characteristics",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "roc.curve.factor"
      ]
    },
    {
      "page": "regression_rrmse",
      "title": "Relative Root Mean Squared Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "rrmse",
        "weighted.rrmse"
      ]
    },
    {
      "page": "regression_rrmse.numeric",
      "title": "Relative Root Mean Squared Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "rrmse.numeric"
      ]
    },
    {
      "page": "regression_rrse",
      "title": "Root Relative Squared Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "rrse",
        "weighted.rrse"
      ]
    },
    {
      "page": "regression_rrse.numeric",
      "title": "Root Relative Squared Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "rrse.numeric"
      ]
    },
    {
      "page": "regression_rsq",
      "title": "r^2",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "rsq",
        "weighted.rsq"
      ]
    },
    {
      "page": "regression_rsq.numeric",
      "title": "r^2",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "rsq.numeric"
      ]
    },
    {
      "page": "classification_shannon.entropy",
      "title": "Shannon Entropy",
      "concept": [
        "Classification",
        "Entropy",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "shannon.entropy"
      ]
    },
    {
      "page": "classification_shannon.entropy.matrix",
      "title": "Shannon Entropy",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "shannon.entropy.matrix"
      ]
    },
    {
      "page": "regression_smape",
      "title": "Symmetric Mean Absolutte Percentage Error",
      "concept": [
        "Machine learning",
        "Performance evaluation",
        "Regression",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "smape",
        "weighted.smape"
      ]
    },
    {
      "page": "regression_smape.numeric",
      "title": "Symmetric Mean Absolutte Percentage Error",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "smape.numeric"
      ]
    },
    {
      "page": "classification_specificity",
      "title": "Specificity",
      "concept": [
        "Classification",
        "Machine learning",
        "Performance evaluation",
        "Statistical learning",
        "Supervised Learning"
      ],
      "topics": [
        "selectivity",
        "specificity",
        "tnr",
        "weighted.selectivity",
        "weighted.specificity",
        "weighted.tnr"
      ]
    },
    {
      "page": "classification_specificity.cmatrix",
      "title": "Specificity",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "specificity.cmatrix"
      ]
    },
    {
      "page": "classification_specificity.factor",
      "title": "Specificity",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "specificity.factor"
      ]
    },
    {
      "page": "classification_weighted.accuracy.factor",
      "title": "Accuracy",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "weighted.accuracy.factor"
      ]
    },
    {
      "page": "classification_weighted.auc.pr.curve.factor",
      "title": "Area under the Precision Recall Curve",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "weighted.auc.pr.curve.factor"
      ]
    },
    {
      "page": "classification_weighted.auc.roc.curve.factor",
      "title": "Area under the Receiver Operator Characteristics Curve",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "weighted.auc.roc.curve.factor"
      ]
    },
    {
      "page": "classification_weighted.baccuracy.factor",
      "title": "Balanced Accuracy",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "weighted.baccuracy.factor"
      ]
    },
    {
      "page": "classification_weighted.brier.score.matrix",
      "title": "Brier Score",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "weighted.brier.score.matrix"
      ]
    },
    {
      "page": "regression_weighted.ccc.numeric",
      "title": "Concordance Correlation Coefficient",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "weighted.ccc.numeric"
      ]
    },
    {
      "page": "classification_weighted.ckappa.factor",
      "title": "Cohen's kappa-Statistic",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "weighted.ckappa.factor"
      ]
    },
    {
      "page": "classification_weighted.cmatrix.factor",
      "title": "Confusion Matrix",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "weighted.cmatrix.factor"
      ]
    },
    {
      "page": "regression_weighted.deviance.gamma.numeric",
      "title": "Gamma Deviance",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "weighted.deviance.gamma.numeric"
      ]
    },
    {
      "page": "regression_weighted.deviance.poisson.numeric",
      "title": "Poisson Deviance",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "weighted.deviance.poisson.numeric"
      ]
    },
    {
      "page": "regression_weighted.deviance.tweedie.numeric",
      "title": "Tweedie Deviance",
      "concept": [
        "Machine learning performance evaluation"
      ],
      "topics": [
        "weighted.deviance.tweedie.numeric"
      ]
    },
    {
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