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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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2 answers
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Machine learning benchmarks: MAE, RMSE, and R-squared

I'm working on a machine learning problem, and I'm having trouble interpreting different measures of model performance. I have a single dependent variable (proportion change between two treatments, ...
S. Robinson's user avatar
0 votes
1 answer
26 views

Why multiple linear regression perform better than single layer neural network in predicting time?

I am doing research on predicting failing time of a component of a machine. Response is failing time of the component of a machine, and the input is location information (consists of integers). I fit ...
wildcat's user avatar
1 vote
1 answer
62 views

Benchmark machine-learning model in MLR3 with randomized data

I am conducting machine-learning in R using mlr3. I would like to assess the performance of my model by conducting a benchmark of my model using real and also randomized data. Here is an example: <...
user374497's user avatar
0 votes
0 answers
34 views

normal qq plot and OLS

Just have a quick question. You have to know by looking at the residual plot and the normal qq plot that the residual should be distributed as normal, average of residuals should be 0 and residuals ...
user398060's user avatar
0 votes
0 answers
57 views

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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0 votes
0 answers
105 views

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
  • 13
0 votes
0 answers
87 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
148 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
1 vote
0 answers
695 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
0 votes
0 answers
50 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
218 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)...
Snedron's user avatar
  • 31
1 vote
1 answer
361 views

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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0 votes
1 answer
233 views

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 ...
purod's user avatar
  • 305
0 votes
1 answer
34 views

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 ...
Nishant 's user avatar
3 votes
0 answers
1k views

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 ...
2 votes
1 answer
7k 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
522 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
  • 165
2 votes
2 answers
521 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
  • 23
2 votes
3 answers
60 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
  • 21
0 votes
1 answer
412 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
  • 305
1 vote
1 answer
337 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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1 vote
0 answers
782 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
565 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 ...
jokel's user avatar
  • 2,773