New answers tagged boosting
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Is there a way to enforce factor importance in random forest/xgboost
If you want to manipulate model into displaying desired feature importances regardless of the importance, that would have resulted from an honest training, you may try to tinker with Cost Efficient ...
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XGBoost Calibration for weighted loss function
If you are doing the one vs. rest approach you are essentially doing calibration for a binary problem. The idea behind this is to get predictions which are as close as possible to the conditional ...
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Cluster analysis with boosting models for better predictions?
As has been pointed out, using clustering as a feature engineering step is common practice. If you think you have discreet clusters present in your data and those meaningfully contribute to your ...
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Why is there no improvement when training Xgboost with pseudo-Huber loss?
There is no definite answer at this but I would note one major and one minor point:
The major point is that: A XGBoost booster starts with a base_score. That is ...
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How to interpret the deviance plot by boosting models
Deviance is a measure of model quality typically (but, I suppose, not necessarily) related to the likelihood. The lower the deviance, the better the model fit. Perhaps think of it this way: models are ...
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Accepted
Ordinal log-loss in a multiclass classification in XGBoost?
For a start, you these packages (whether we're talking xgboost or lightgbm or whatever) are almost certainly working with non-softmaxed logits. You can see that by e.g. getting them for a trained ...
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Multivariate Time Series dataset preparation
The correct way to use your input data depends on the way it was collected. In general, you can only use features for which the values are known before the model should forecast and this is usually ...
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Ordinal vs multinominal classification in XGboost: differences in one-hot encoding
I think you are hitting undetermined behaviour here as XGBoost is not designed to have y be a pandas.DataFrame. I suspect that ...
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Accepted
Help with Classification model for S&P500
There’s a huge issue in what you’re doing that need to have attention drawn to it.
I also created a weight variable which is the absolute value of the return, which I would use as input for xgboost.
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Do Boosted tree models result in only one final tree?
As the other answer mentions, the direct result is a collection of trees.
Depending on the operation used to combine trees, however, these can be combined into a single tree spanning the whole ...
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Estimating expected lifetime from hazard ratio and estimated base hazard function
You may want to check out the work of Haybittle/Pollard who give a good formula for estimating using the Gompertz function:
Life Expectancy at age x = 1/k * ln((1+k/h(x)) - 1/2 (1+ h(x)/k)^-2)
k = 0....
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