Questions tagged [xgboost]

For questions related to the eXtreme Gradient Boosting algorithm.

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28 views

if new feature downgrade the score for xgboost what do I have to look at?

let say I'm predicting the housing price of Boston(kaggle). if I got some score x then I added new feature y_K if this new feature drop the score. what is wrong with this feature and what do I ...
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62 views

Why am I getting accuracy of Xgboost model 0.00%?

I am trying to build Job Recommender System using Deep Learning. dataset used From this dataset i have taken only users.tsv, user_history.tsv, apps.tsv and jobs.tsv to build a hybrid recommender ...
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62 views

How do I train Xgboost classifier for ECG Signal data?

I am testing https://www.physionet.org/challenge/2017/sources/ submission. I like one of the submission code, which use Xgboost to train the classifier. Training ...
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45 views

Model Performance using Precision as evaluation metric

I am dealing with an imbalanced class with the following distribution : (Total dataset size : 10763 X 20) 0 : 91% 1 : 9% To build model on this dataset having class imbalance, I have compared ...
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48 views

Problem about tuning hyper-parametres

I have tried GridSearchCV and BayesSearchCV for tuning my LightGBM algorithm (for binary classification). I have used 10 iterations and I have indicated scoring ="roc_auc" In the first iteration, I ...
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138 views

How does L1 Loss work in lightGBM

From the paper, lightGBM does a subsampling according to sorted $|g_i|$, where $g_i$ is the gradient (for the loss function) at a data instance. My question is that, when the objective is L1 loss/...
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22 views
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1answer
494 views

Using a combination of gradient boosting with LSTM for classification?

I am presently using an LSTM model to classify high dimensional tabular data which is not text/images (dimensions 21392x1970). I also tried XGBoost (Gradient boosting) in Python separately for the ...
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305 views

Xgboost rank:ndcg learning per group or for all dataset

I'm trying to implement xgboost with an objective of rank:ndcg I want the target to be between 0-3. In my data for most of the groups, there is only 1 event per ...
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42 views

Using feature vectors from imagenet to train xgboost (vs a standard Conv net)?

I am planning to use feature vectors generated from imagenet to train an xgboost model. This is as opposed to training a standard convolutional network with the same image set. This is because we ...
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93 views

What would be the equivalent of R's mboost in Python?

I am looking for the Python equivalent of R's mboost package ( mboost ). Would that be xgboost?
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306 views

Comparing XGBR with CatBoost performance

I saw on a CatBoost site that it supposed to outperform any other boosted training model and decided to try it myself on a Kaggle's https://www.kaggle.com/c/house-prices-advanced-regression-techniques....
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291 views

xgboost gain vs kolmogorov smirnov

After running xgboost model with: objective = 'binary:logistic' eval_metric = 'logloss' I have a group of 3 variables that have the highest values of gain. Now, ...
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86 views

Regression Decision Tree - Normalize or Split into Ranges a continuos feature

I have in my dataset a feature named distances which ranges goes from 200 to 12000 (more or less). Since the other features have got values under 50 I need to do ...
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1answer
155 views

Can you reuse observations from your train data in your final test data?

For an employee population, I am trying to determine who among the employees are likely to get injured in the future based on 2 years worth of data. Unlike in most machine learning problems where you ...
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43 views

AdaBoost - Ensemble model perform poor than best weak classifier

Can Adaboost's ensemble classifier perform worse than the best of the weak learners considered? If so when in what case of weak learner the ensemble learning does not perform better?
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2k views

xgboost f-score

I'm using xgboost package on python 3.5 for time base predication The result of the f-score Partial dependence on the order of the columns in data frame. The rmse of the predication is a same. for ...
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98 views

separate decision tree for categorical feature values

Given either, different decision trees each based on a particular feature value (like separate models for each male and female) or a single decision tree, should both give the same result?
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196 views

How does XGBoost implement MAE loss?

As we all know, XGBoost constructs trees based on gradient. I wonder how does XGBoost define gradient of MAE loss, as MAE itself is not differentiable. After some digging of the source code, I found ...
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34 views

What gradient boosting library is the easiest to implement on mobile?

I think of implementing training and predicting in an app (both Android and iOS), but existing packages I found not seem to be very mobile-friendly (scikit-learn, xgboost, lightgbm). Random forest ...
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474 views

How to interpret continuous variables in a decision tree model?

After fitting a decision tree with some continuous variable, how do I interpret the effect that variable has on the target? For example I'm predicting target Y. From sklearn random forest or Xgboost ...
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397 views

xgboost - How do I treat document ID in pairwise ranking

I am trying to use xgboost in R for pairwise ranking for an implicit dataset. For simplicity, let's assume that I am dealing with a search problem, where I want to rank documents relative to a given ...
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599 views

XGBoost: predict on only valuable features

I have a somewhat strange case that I can't find an answer to anywhere. It is really only applicable if you have a legitimately large data set. Let me describe. XGBoost returns feature importance for ...
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62 views

Injecting random values as one input feature for feature selection results in a odd beaviour

I am trying to find a cutoff value, in the feature importance space to eliminate spurious features. So I am injecting a completely random generated feature (as one of the input features) and I cut the ...
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344 views

How to set subsample in lightgbm in R?

There is a subsample parameter for the XGBoost (xgb.train() function in R). What is the corresponding subsample parameter for ...
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672 views

Feeding data to Xgboost for recomender system

I am using xgboost for a recommender system. There are 3-4 recommended content on each page. My data consists of columns like page_id and advertisement_id. Currently for every page_id, there are 3-4 ...
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280 views

What does “gblinear” do in XGBoost?

For example, if I run a single round (nrounds=1), how does XGBoost go about making predictions? I thought it would simply return a linear regression model, but I ...
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508 views

Why initialization of Xgboost DMatrix reducec features number?

I am trying to understand following case: when I create new xgbost DMatrix xgX = xgb.DMatrix(X, label=Y, missing=np.nan) ...
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2answers
173 views

Xgboost in R: Dealing with extreme class imbalance

My data has an extreme class imbalance - 99.7% is 0's and 0.2% is 1's and almost all the predictor variables (6 out of 7) are categorical. I trained an xgboost classifier after performing an ...
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1answer
142 views

XGBOOST missing_value feature degrades my performance?

I'm training an xgboost model for gout disease on a training set I sampled 1-to-7 case-control ratio (enriched in cases). I have 220 features and I reach a cross-...
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20 views

Multi-output classifier using Tensorflow/Keras on tabular data

I have been tasked with combining a several classifier models we have into one model using deep learning (or something else). The reason for this is that, in future, it would be difficult to maintain ...
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22 views

Changing objective functions with penalty term in XGboost in R

I basically have something like: ...
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43 views

Examples of the use of xgboost for recommender systems?

Are there any state-of-the-art implementations of xgboost in recommender systems? I'm looking for GitHub implementations but also papers that discuss this. I've only found this paper https://...
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56 views

Prediction error without having a true value

Quick summary about the problem: we are trying to deploy our regression model, where the clients require "individual prediction error". Since we're predicting something unknown in advance, we can't ...
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24 views

Why XGBoost regressor predicts behavior but not the amplitude?

I am very new to machine learning and I am trying to use XGBoostRegressor for my machine learning model (it has to do with physical modeling). I found out that it works very well for predicting the ...
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22 views

Should the LightGBM score match the regularization?

If I set the parameter objective to regression_l1 and set the metric to mean absolute error in ...
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138 views

XGBoost for multi-label image classification

I am trying to use the xgboost classifier for a multi-label and multi-class image classification task. I have a list of images that can have up to 5 different labels in each of them. Before I use the ...
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20 views

Feature engineering ideas with dates, coordinates and other variables

I'm working on an ETA problem where I'm trying to estimate a time of arrival for a delivery. I have coordinates of pickup/destination, time of pick , infos about the rider, some other variables that ...
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72 views

Suggestion for handling specific missing data

I have data, that describes distance from given location to nearest object (e.g. school, shop etc). Because of performance reasons I couldn't scrape the data about objects, that are futher away than 2....
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12 views

Improve the results of imbalanced multi-classification multi-lables data

I have 10k rows of multi-classification (x1..x27,y), size of dataframe is: 28*10k and its ...
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17 views

Data Transformation Tips for xgboost's XGBClassifier

I have this X_train and test distribution for the 4 features 'X', 'Y', 'TX' and 'TY'. I realize the range of the distribution is widely varying .. Can you suggest a good way to clean/ transform that ...
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28 views

if I got feature importance of xgboost/LightGBM what is next?

If I have feature importances of different variables in a xgboost/LightGBM model, how do I use this information? Is it better to just use the top n features and retrain the model? Does the feature ...
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20 views

What is the best approach to train a multi-category regression model?

What is the best approach to train a multi-category regression model (using XBoost decision trees ensemble)? What are the ups and downs of each one? For example, if I want to train a model to predict ...
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1answer
26 views

Predict items customers would buy in next order

I am working on a time series classification problem to identify what items customers would buy in their next order (customers orders different products every week). Let's say we have a customer who ...
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1answer
48 views

How to restructure my dataset for interpretability without losing performance?

What I am doing: I am predicting product ratings using boosted trees (XGBoost) with a dataset in this format: What I want to do: I want to use SHAP TreeExplainer to interpret each prediction my ...
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10 views

How to encode features that encode regular values as well as special categorical values

I was recently playing around with the FICO explainable machine learning challenge dataset. In the dataset, there are a bunch of numerical features which have values values typically in the 0-100 ...
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1answer
104 views

Specifying number of threads using XGBoost.train

When using the xgboost.train() function, all the threads are used. I would like to use a specific amount. Unfortunately, this function does not accept the ...
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2answers
71 views

Compare scores of models

We got several models with predictions. How can we compare scores of different models with each other? We assume that we got xgboost models and scores distribution can be different for each model, so ...
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104 views

Save xboost model from R as Python pickle

I trying save R model to pickle, but I getting error Evaluation error: Unable to convert R object to Python type. ...
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2answers
40 views

Xgboost take k best predictions

I have a mission of classification with a lot of classes. I am comparing some ML algorithms for this case and I would like to try xgboost. I am writing in python and I am trying to get the best 3 ...