tks0123456789 / XGBoost_vs_LightGBM

Comparison of XGBoost and LightGBM (speed, accuracy and complexity)

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Comparisons of XGB[0.81] and LGB[2.2.1]

  • LightGBM.ipynb: Modified version of marugari's work

  • exp013

    • model : XGB(hist_depthwise, hist_lossguie, hist_GPU, GPU), LGB
    • objective : Binary classification
    • metric : Logloss
    • dataset : make_classification
    • n_train : 0.5M, 1M, 2M
    • n_valid : n_train/4
    • n_features : 32
    • n_clusters_per_class : 8
    • n_rounds : 100
    • max_depth : 5, 10, 15
    • num_leaves : 2 ** max_depth
  • exp014

    • model : XGB(hist_depthwise, hist_lossguie, hist_GPU, GPU), LGB
    • objective : Binary classification
    • metric : Logloss
    • dataset : make_classification
    • n_train : 1,2,4,8,16,32 * 10K
    • n_valid : n_train/4
    • n_features : 256
    • n_clusters_per_class : 8
    • n_rounds : 100
    • max_depth : 5, 10
    • num_leaves : 2 ** max_depth

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Comparison of XGBoost and LightGBM (speed, accuracy and complexity)


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