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Models/Random Forest

Random Forest

Reported on 35 benchmarks across 14 tasks · 4 papers · 16 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing11 results

  • Intrusion DetectiononCICIDS2017
    Accuracy (%)
    98.13
  • Intrusion DetectiononCICIDS2017
    F1 Score (Macro Avg)
    98.13
  • Intrusion DetectiononCICIDS2017
    Precision (Macro Avg)
    98.14
  • Intrusion DetectiononCICIDS2017
    Recall (Macro Avg)
    98.13
  • Intrusion DetectiononCICIDS2017
    Avg F1· uses extra data
    0.971
    best: 0.9875 (OC-SVM / RF)
  • Intrusion DetectiononCICIDS2017
    Precision· uses extra data
    98.2
    best: 99.26 (OC-SVM / RF)
  • Intrusion DetectiononCICIDS2017
    Recall· uses extra data
    96.1
    best: 99.7 (DBN)
  • Entity ResolutiononAbt-Buy
    F1 (%)
    85
    best: 95.78 (gpt4-0613_zeroshot)
  • Entity ResolutiononWDC Computers-xlarge
    F1 (%)
    78
    best: 98.33 (RoBERTa-SupCon)
  • Entity ResolutiononAmazon-Google
    F1 (%)
    79
    best: 85.21 (gpt4-0613_fewshot-10)
  • Text ClassificationonACL-ARC
    F1
    53
    best: 78.1 (FE-MLM + Span)

Methodology9 results

  • Anomaly DetectiononVehicle Claims
    AUC· 2022-10-25
    98.65
    SOTA
    Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical EncodingsarXiv:2210.14056
  • Electrocardiography (ECG)onMIMIC-III
    F1 score· 2018-03-18
    0.97
    SOTA
    Early hospital mortality prediction using vital signalsarXiv:1803.06589
  • Electrocardiography (ECG)onMIMIC-III
    Precision· 2018-03-18
    0.97
    SOTA
    Early hospital mortality prediction using vital signalsarXiv:1803.06589
  • Electrocardiography (ECG)onMIMIC-III
    Recall· 2018-03-18
    0.97
    SOTA
    Early hospital mortality prediction using vital signalsarXiv:1803.06589
  • ClassificationonCoordinated Reply Attacks in Influence Operations: Characterization and Detection
    AUC· 2018-03-18
    0.97
    SOTA
    Early hospital mortality prediction using vital signalsarXiv:1803.06589
  • Medical waveform analysisonMIMIC-III
    F1 score· 2018-03-18
    0.97
    SOTA
    Early hospital mortality prediction using vital signalsarXiv:1803.06589
  • Medical waveform analysisonMIMIC-III
    Precision· 2018-03-18
    0.97
    SOTA
    Early hospital mortality prediction using vital signalsarXiv:1803.06589
  • Medical waveform analysisonMIMIC-III
    Recall· 2018-03-18
    0.97
    SOTA
    Early hospital mortality prediction using vital signalsarXiv:1803.06589
  • ClassificationonACL-ARC
    F1
    53
    best: 78.1 (FE-MLM + Span)

Computer Vision6 results

  • Person Re-IdentificationoneSports Sensors Dataset
    Accuracy· 2020-11-02
    52.1
    SOTA
    Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports DatasetarXiv:2011.00958
  • Person Re-IdentificationoneSports Sensors Dataset
    LogLoss· 2020-11-02
    0.01617
    best: 0.01588 (SVM)
    SOTA
    Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports DatasetarXiv:2011.00958
  • Person Re-IdentificationoneSports Sensors Dataset
    ROC AUC· 2020-11-02
    0.919
    SOTA
    Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports DatasetarXiv:2011.00958
  • Skills EvaluationoneSports Sensors Dataset
    LogLoss· 2020-11-02
    0.456
    best: 0.311 (SVM)
    SOTA
    Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports DatasetarXiv:2011.00958
  • Skills EvaluationoneSports Sensors Dataset
    Accuracy· 2020-11-02
    80
    best: 85.6 (SVM)
    Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports DatasetarXiv:2011.00958
  • Skills EvaluationoneSports Sensors Dataset
    ROC AUC· 2020-11-02
    0.885
    best: 0.945 (SVM)
    Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports DatasetarXiv:2011.00958

Knowledge Base4 results

  • Causal InferenceonIHDP
    Average Treatment Effect Error· 2016-06-13
    0.96
    best: 0.13 (SIP + BCAUSS)
    SOTA
    Estimating individual treatment effect: generalization bounds and algorithmsarXiv:1606.03976
  • Data IntegrationonAbt-Buy
    F1 (%)
    85
    best: 95.78 (gpt4-0613_zeroshot)
  • Data IntegrationonWDC Computers-xlarge
    F1 (%)
    78
    best: 98.33 (RoBERTa-SupCon)
  • Data IntegrationonAmazon-Google
    F1 (%)
    79
    best: 85.21 (gpt4-0613_fewshot-10)

Medical3 results

  • Mortality PredictiononMIMIC-III
    F1 score· 2018-03-18
    0.97
    SOTA
    Early hospital mortality prediction using vital signalsarXiv:1803.06589
  • Mortality PredictiononMIMIC-III
    Precision· 2018-03-18
    0.97
    SOTA
    Early hospital mortality prediction using vital signalsarXiv:1803.06589
  • Mortality PredictiononMIMIC-III
    Recall· 2018-03-18
    0.97
    SOTA
    Early hospital mortality prediction using vital signalsarXiv:1803.06589

Graphs1 result

  • Graph RegressiononTox21
    AUC@80%Train
    0.71
    best: 0.78 (CensNet)

Other1 result

  • Sentence ClassificationonACL-ARC
    F1
    53
    best: 78.1 (FE-MLM + Span)