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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Which test in this case ? Friedman not possible

I have done a benchmarking of multiple learners on multiple tasks with nested CV (inner loop : CV 3F, and outer loop : CV 3F). My datas have 1052 observations and each task have 10-12 features. I ...
Nicolas's user avatar
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Overfitting models in mlr3

I'm trying to compare multiple learners on my dataset (called "data") in order to predict a target called "lesionResponse", with custom resampling. Since mlr3 package doesn't allow ...
Nicolas's user avatar
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MLR and MANOVA with a Correlational Predictive Design?

A very silly question, I am sure. However, can a MANOVA be considered a secondary analysis to MLR as part of a correlation predictive design?
Nick's user avatar
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Tune threshold in hyperparameter tuning is giving worse results in MLR

First, I tried not tuning the hyperparameters without setting tune.threshold=TRUE. ...
11thal11thal's user avatar
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78 views

How to select features while keeping covariates in mlr3

I am doing a classification job using mlr3. There are several covariates besides independent variables (features) in my dataset. I wonder how to select a feature ...
YiweiZhu's user avatar
2 votes
1 answer
135 views

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 ...
Eduardo A. Sánchez Torres's user avatar
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627 views

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: ...
agnesg2g's user avatar
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46 views

Difference in resample MSE from mlr3

I created a new task with TaskRegr$new, a learner with lrn('regr.ranger'), a search space with ...
Dean MacGregor's user avatar
3 votes
1 answer
183 views

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 ...
korolev's user avatar
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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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1 answer
6k views

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 ...
Olivia Heino's user avatar
1 vote
1 answer
499 views

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 ...
user51462's user avatar
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2 answers
417 views

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 ...
vk1233's user avatar
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2 votes
3 answers
59 views

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 ...
ummmm's user avatar
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1 answer
379 views

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 ...
purod's user avatar
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328 views

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, ...
Jan Vo's user avatar
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10 votes
1 answer
2k views

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 ...
Mooks's user avatar
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631 views

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 ...
B. van der Wal's user avatar
1 vote
1 answer
554 views

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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