Questions tagged [mlr]

"mlr" is an R Package focussing on machine learning. The abbreviation "mlr" stands for "machine learning in R"

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Model assumption to evalute and graph used to evalute each assumption

When I have to fit a MLR model of bwt on 3 variables (lwt, age, smoke) , before evaluating the model, including at the overall fit using R^2 adju. and looking at the interval estimates of their model ...
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Parameter 'C' cannot be optimized for 'nu-svr'? mlr3 with kernlab

I am trying to optimize an SVR model within the mlr3 ecosystem with the kernlab package and I am getting the following error: The parameter 'C' can only be set if ...
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Error "Feature names stored in `object` and `newdata` are different!" using xgboost in mlr package [closed]

I am trying to make a multilabel classification model for XGBoost. I have one that works for RF, but when I try this code below for XGBoost I get the error: ...
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Difference in resample MSE from mlr3

I created a new task with TaskRegr$new, a learner with lrn('regr.ranger'), a search space with ...
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Multiple Linear Regression with more variables than samples

I'm currently learning chemometrics for my work and I have a simple question about Multiple Linear Regression (MLR). Just to explain the context: I am simply using UV-Vis-NIR spectra (2500 wavelengths)...
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Why does the accuracy of leave-one-out CV change between runs for my kNN task?

I'm getting into ML, working through the book Machine Learning with R, the Tidyverse and MLR. Early on the concept of cross validation is introduced as a means to gauge the ability of my model to work ...
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What is the default feature importance for classif.randomForestSRC in mlr?

Below is the code I used, "ano.cla.filter" is a filtering method defined by myself ...
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How to get boundary points that are at interface of differnet classes in multilabel classification dataset

I am working on finding points which are at boundary of different classes. In other words finding points on which a classifier would be most confused or uncertain about. For a setting like multi label ...
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R alternative to scikit-learn [closed]

As a statics researcher, I've been using R since university and I know it quite well, I also know that it's immediate, but it quickly gets chaotic, and this also happens because of the variety and ...
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Making a residual plot in multiple linear regression

I need to make a residual plot and I was wondering whether I make the plots in multiple linear regression on one independent variable at a time (like making a simple linear regression) or the all of ...
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R mlr - How does tuneThreshold work?

I would like to tune the threshold for the following classification task using tuneThreshold in conjunction with a learner parameter. I first tried to tune the ...
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How do I fit models with predetermined covariates?

I'm trying to fit a multiple linear regression model. It has 10 variables, 2 of which are specified (e.g. $\beta_4 = 0.5$, $\beta_7 = 0.77$). How do I go about fitting this in R? I need to find the ...
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Multiple regression results help

For my first ever research paper I've run a hierarchal multiple linear regression with two predictors and one outcome variable, however I don't understand my results. I've found predictor A to be a ...
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How could I do parameter tuning with feature selection in R package mlr?

In this project, I am trying to tune the parameters(especially the step number parameter) of the CoxBoost model for survival analysis. I have more features than samples and many features are highly ...
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Predicting house pricing using MLR

My problem I want to predict housing prices in a city (for an upcoming year). My solution Create a MLR, where average housing price is dependent and macroeconomic fundamentals (population, gdp, ...
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mlr compared to caret

I’ve been using mlr a little to learn about machine learning, but recently found out about caret. The way I understand it is that both are wrappers to various ML packages, but have slightly different ...
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Poor model fit - Difference between SEM and MLR

For a study I am researching a quite simple research model (7 IVs - 1 DV), in which I am not interested in underlying relations between the IVs: the relation between the IVs and the DV is all that ...
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Generate ensemble of classifiers based on predefined feature subsets in R using mlr

I would like to create an ensemble classifier for a dataset and use different classification models for different subsets of features (these feature subsets are predefined as the data set I am working ...
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