Interpretable machine learning with an ensemble of gradient boosting machines von Konstantinov, Andrei V., Utkin, Lev V.

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An imprecise deep forest for classification von Utkin, Lev V.

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Attention-based random forest and contamination model von Utkin, Lev V., Konstantinov, Andrei V.

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SurvLIME: A method for explaining machine learning survival models von Kovalev, Maxim S., Utkin, Lev V., Kasimov, Ernest M.

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Uncertainty Interpretation of the Machine Learning Survival Model Predictions von Utkin, Lev V., Zaborovsky, Vladimir S., Kovalev, Maxim S., Konstantinov, Andrei V., Politaeva, Natalia A., Lukashin, Alexey A.

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A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov–Smirnov bounds von Kovalev, Maxim S., Utkin, Lev V.

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A Siamese Deep Forest von Utkin, Lev V., Ryabinin, Mikhail A.

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Multi-attention multiple instance learning von Konstantinov, Andrei V., Utkin, Lev V.

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SurvNAM: The machine learning survival model explanation von Utkin, Lev V., Satyukov, Egor D., Konstantinov, Andrei V.

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Improving over-fitting in ensemble regression by imprecise probabilities von Utkin, Lev V., Wiencierz, Andrea

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A robust weighted SVR-based software reliability growth model von Utkin, Lev V., Coolen, Frank P.A.

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A deep forest classifier with weights of class probability distribution subsets von Utkin, Lev V., Kovalev, Maxim S., Meldo, Anna A.

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Interpretable ensembles of hyper-rectangles as base models von Konstantinov, Andrei V., Utkin, Lev V.

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The imprecise Dirichlet model as a basis for a new boosting classification algorithm von Utkin, Lev V.

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An one-class classification support vector machine model by interval-valued training data von Utkin, Lev V., Zhuk, Yulia A.

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A weighted random survival forest von Utkin, Lev V., Konstantinov, Andrei V., Chukanov, Viacheslav S., Kots, Mikhail V., Ryabinin, Mikhail A., Meldo, Anna A.

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Fuzzy One-Class Classification Model Using Contamination Neighborhoods von Utkin, Lev V.

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A framework for imprecise robust one-class classification models von Utkin, Lev V.

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Binary classification SVM-based algorithms with interval-valued training data using triangular and Epanechnikov kernels von Utkin, Lev V., Chekh, Anatoly I., Zhuk, Yulia A.

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Improvement of the Deep Forest Classifier by a Set of Neural Networks von Utkin, Lev V., D. Zhuk, Kirill

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