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    {
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      "votes": 123
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      "votes": 621
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      "ref": "tomehta/lasso-for-feature-selection-and-logreg",
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      "ref": "shashanksagarjha/feature-scaling-modelling-and-hyperparameter",
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    {
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      "votes": 9
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    {
      "ref": "gravix/elastic-fit",
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    {
      "ref": "ashishpatel26/which-model-is-best-check-out",
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    {
      "ref": "zahaviguy/simple-feature-selection-with-r-auc-0-830",
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      "votes": 13
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      "ref": "tboyle10/feature-selection",
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    {
      "ref": "vincentlugat/logistic-regression-rfe",
      "votes": 104
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    {
      "ref": "xsakix/first-overfit",
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      "ref": "shadabhussain/avoid-overfitting",
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      "ref": "ashishpatel26/starter-automl-don-t-overfit",
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      "votes": 940
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      "ref": "anand0427/overfit-submission",
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      "ref": "magf46/can-we-predict-if-the-data-is-from-train-or-test",
      "votes": 1
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      "ref": "suhail511/don-t-overfit",
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    {
      "ref": "ukkoa1/first-kernel-rf-w-boruta-selection-and-caret",
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      "votes": 4
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    {
      "ref": "miroslavsabo/auc-0-844-in-11-loc",
      "votes": 49
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    {
      "ref": "robikscube/don-t-overfit-ii-first-look-and-eda",
      "votes": 27
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      "ref": "takaishikawa/experiment02-corr-select-logistic-reg",
      "votes": 11
    },
    {
      "ref": "bigkizd/lightgbm-with-cross-validation",
      "votes": 10
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    {
      "ref": "nadare/simple-logistic-regression-with-l1-penalty",
      "votes": 31
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    {
      "ref": "rodasoares/correlation-matrix-randomforestregressor",
      "votes": 4
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    {
      "ref": "gaurav146/don-t-overfit",
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    {
      "ref": "jahaziel/simple-model-glmnet",
      "votes": 90
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    {
      "ref": "lukebassett/do-2-corr-logistic-regression-experimentation",
      "votes": 4
    },
    {
      "ref": "jazivxt/over-the-top-hawk-s-journey",
      "votes": 6
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      "votes": 7
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      "votes": 134
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}