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Questions tagged [boosting]

Boosting is a machine learning ensemble meta-algorithm in supervised learning, and a family of machine learning algorithms that convert weak learners to strong ones. Also: Boosting is the process of enhancing the relevancy of a document or field

From [the docs]:

"Boosting" is a machine learning ensemble meta-algorithm for primarily reducing bias, and also variance in supervised learning, and a family of machine learning algorithms that convert weak learners to strong ones.

Also:

From the docs:

Boosting is the process of enhancing the relevancy of a document or field. Field level mapping allows to define an explicit boost level on a specific field. The boost field mapping (applied on the root object) allows to define a boost field mapping where its content will control the boost level of the document.

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Making sense of gbm survival prediction model

I am a newbie in using and making sense of ML methods and currently doing survival analysis using gbm package in R. I have difficulty understanding some of the output of the survival prediction model. I have checked this tutorial and this post but…
Amer
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Identical predictions in XGBoost

When I've used XGBoost for regression in the past, I've gotten differentiated predictions, but using an XGBClassifier on this dataset is resulting in all cases being predicted to have the same value. The true values of the test data are that 221…
Laura
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R: how to improve gradient boosting model fit

I tried fitting a gradient boosted model (weak learners are max.depth = 2 trees) to the iris data set using gbm in the gbm package. I set the number of iterations to M = 1000 with a learning rate of learning.rate = 0.001. I then compared the results…
Adrian
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How to conduct catboost grid search using GPU in R?

I'm setting up a grid search using the catboost package in R. Following the catboost documentation (https://catboost.ai/docs/), the grid search for hyperparameter tuning can be conducted using the 3 separate commands in R, fit_control <-…
ML Soil
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Which (ML/DL) model is best for multi class classification for smaller datasets?

I am working with health dataset. The dataset is about body signals (8 features) and the target variable is body failing Temperature. There were 6 different temperatures or Multi classes. (targets) My data set is of shape (1500*9) - Numerical…
Mari
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Can I use XGBoost to boost other models (eg. Naive Bayes, Random Forest)?

I am working on a fraud analytics project and I need some help with boosting. Previously, I used SAS Enterprise Miner to learn more about boosting/ensemble techniques and I learned that boosting can help to improve the performance of a…
Jane
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how to Joint feature via online boosting

I would like to combine two features using online boosting. I read more papers that explain online boosting and joint features using boosting, papers are: Identification of a specific person using color, height, and gait features for a person…
Algabri
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Boosting (ensemble learning) graphs of error vs number of trees show an incorrect trend

I am running boosting over a standard dataset (Abalone), using both SAMME and SAMMME.R algorithms of boosting and the graphs that I obtained are not what I was expecting. It is a multi-class classification problem using supervised learning. Here is…
amiageek
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ValueError("x and y must be the same size")

import pandas as pd import numpy as np import re import seaborn as sns import matplotlib.pyplot as plt import seaborn as sns import xgboost as xgb from xgboost import XGBClassifier from sklearn.ensemble import GradientBoostingClassifier from…
Vishnu vardhan
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Using datetime64 feature type in building a model?

I have a dataframe which includes around 50 features. In my experiment I have a classification problem so I want to train the model by "GradientBoostingClassifier". The dataframe (mydata) is considered as a training set. One of those 50 features…
Spedo
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Questions around XGBoost

I am trying to understand the XGBoost algorithm and have a few questions around it. I have read various blogs but all seem to tell a different story. Below is a snippet from the code that I am using (only for reference). param <- list( objective …
Prince
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How do AdaBoost.MM compare with SAMME/SAMME.R?

I want to know whether there are works on empirical comparison between two multi-class AdaBoost algorithms, AdaBoost.MM proposed in the paper "A Theory of Multiclass Boosting" (section 8) and SAMME/SAMME.R proposed in "Multi-class AdaBoost". The…
Yi Huang
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How to get predict probabilities from Sklearn Gradient Boosting Classifier using individual estimators?

I'm trying to find out how sklearn's gradient boosting classifier makes predictions from the different estimators. I want to translate the sklearn model into base python to perform predictions. I know how to get the individual estimators from the…
Theoaf
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When using the scale_pos_weight parameter in xgboost, I don't know why this is happening?

I have to solve the binary classification problem. (The ratio of train data size betweens label 0 and 1 is 4.7: 1) So, I created the model with the xgboost algorithm. Result is quite good. - AUC: 0.989 - Precision(0/1): 0.998 / 0.938 - Recall(0/1):…
gomcheol
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Problem in residual plot of a Regression XGBoost model

I'm using xgboost to build a regression tree. I"m doing a GridSearch to find the optimal parameters. My training set has around 800 instances and I'm doing a CV = 3. Once the model is built, I see some issues in the residual plots. This is how the…
HHH
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