13 citations · 23 across the 8 of their papers we have counts for
9 papers
On the Relation between Prediction and Imputation Accuracy under Missing Covariates
Burim Ramosaj, Justus Tulowietzki, Markus Pauly
Missing covariates in regression or classification problems can prohibit the direct use of advanced tools for further analysis. Recent research has realized an increasing trend tow…
Interpretable Machines: Constructing Valid Prediction Intervals with Random Forests
Burim Ramosaj
An important issue when using Machine Learning algorithms in recent research is the lack of interpretability. Although these algorithms provide accurate point predictions for vario…
Universal Approximation Theorems of Fully Connected Binarized Neural Networks
Mikail Yayla, Mario Günzel, Burim Ramosaj +1
Neural networks (NNs) are known for their high predictive accuracy in complex learning problems. Beside practical advantages, NNs also indicate favourable theoretical properties su…
Goodness (of fit) of Imputation Accuracy: The GoodImpact Analysis
Maria Thurow, Florian Dumpert, Burim Ramosaj +1
In statistical survey analysis, (partial) non-responders are integral elements during data acquisition. Treating missing values during data preparation and data analysis is therefo…
Asymptotic based bootstrap approach for matched pairs with missingness in a single-arm
Lubna Amro, Markus Pauly, Burim Ramosaj
The issue of missing values is an arising difficulty when dealing with paired data. Several test procedures are developed in the literature to tackle this problem. Some of them are…
Asymptotic Unbiasedness of the Permutation Importance Measure in Random Forest Models
Burim Ramosaj, Markus Pauly
Variable selection in sparse regression models is an important task as applications ranging from biomedical research to econometrics have shown. Especially for higher dimensional r…
Consistent Estimation of Residual Variance with Random Forest Out-Of-Bag Errors
Burim Ramosaj, Markus Pauly
The issue of estimating residual variance in regression models has experienced relatively little attention in the machine learning community. However, the estimate is of primary in…
A cautionary tale on using imputation methods for inference in matched pairs design
Burim Ramosaj, Lubna Amro, Markus Pauly
Imputation procedures in biomedical fields have turned into statistical practice, since further analyses can be conducted ignoring the former presence of missing values. In particu…
Who wins the Miss Contest for Imputation Methods? Our Vote for Miss BooPF
Burim Ramosaj, Markus Pauly
Missing data is an expected issue when large amounts of data is collected, and several imputation techniques have been proposed to tackle this problem. Beneath classical approaches…