4 papers
Fitting Multiple Machine Learning Models with Performance Based Clustering
Mehmet Efe Lorasdagi, Ahmet Berker Koc, Ali Taha Koc +1
Traditional machine learning approaches assume that data comes from a single generating mechanism, which may not hold for most real life data. In these cases, the single mechanism…
Binary Feature Mask Optimization for Feature Selection
Mehmet E. Lorasdagi, Mehmet Y. Turali, Suleyman S. Kozat
We investigate feature selection problem for generic machine learning models. We introduce a novel framework that selects features considering the outcomes of the model. Our framew…
AFS-BM: Enhancing Model Performance through Adaptive Feature Selection with Binary Masking
Mehmet Y. Turali, Mehmet E. Lorasdagi, Ali T. Koc +1
We study the problem of feature selection in general machine learning (ML) context, which is one of the most critical subjects in the field. Although, there exist many feature sele…
Hierarchical Ensemble-Based Feature Selection for Time Series Forecasting
Aysin Tumay, Mustafa E. Aydin, Ali T. Koc +1
We introduce a novel ensemble approach for feature selection based on hierarchical stacking for non-stationarity and/or a limited number of samples with a large number of features.…