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Imputation by feature importance (IBFI): A methodology to envelop machine learning method for imputing missing patterns in time series data

PloS one, 2022-01, Vol.17 (1), p.e0262131

2022

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Anomaly Classification for Earthquake Prediction in Radon Time Series Data Using Stacking and Automatic Anomaly Indication Function

Pure and applied geophysics, 2021-05, Vol.178 (5), p.1593-1607

2021

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Simulated Annealing-Based Image Reconstruction for Patients With COVID-19 as a Model for Ultralow-Dose Computed Tomography

Frontiers in physiology, 2022-01, Vol.12, p.737233-737233

2022

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Time Series Reconstruction With Feature-Driven Imputation: A Comparison of Base Learning Algorithms

IEEE access, 2024, Vol.12, p.85511-85530

2024

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Correction to: Anomaly Classification for Earthquake Prediction in Radon Time Series Data Using Stacking and Automatic Anomaly Indication Function

Pure and applied geophysics, 2021-06, Vol.178 (6), p.2395-2395

2021

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Analysis of Proposed and Traditional Boosting Algorithm with Standalone Classification Methods for Classifying Gene Expresssion Microarray Data Using a Reject Option

Applied artificial intelligence, 2022-12, Vol.36 (1)

2022

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An Improved Imputation Method for Accurate Prediction of Imputed Dataset Based Radon Time Series

IEEE access, 2022, Vol.10, p.20590-20601

2022

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A Novel Hybrid Learning System Using Modified Breaking Ties Algorithm and Multinomial Logistic Regression for Classification and Segmentation of Hyperspectral Images

Applied sciences, 2021-08, Vol.11 (16), p.7614

2021

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Classification of rocks radionuclide data using machine learning techniques

Acta geophysica, 2018-10, Vol.66 (5), p.1073-1079

2018

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Imputation by feature importance

PloS one, 2022-01, Vol.17 (1), p.e0262131

2022

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Multifractal detrended cross-correlation analysis of radioactivity borne radon, thoron and meteorological time series

Physica A, 2022-12, Vol.607, p.128214, Article 128214

2022

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K-means and K-medoids: Cluster Analysis on Birth Data Collected in City Muzaffarabad, Kashmir

IEEE access, 2020-01, Vol.8, p.1-1

2020

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Comparative Analysis of Boosting with other Machine Learning Methods for classifying Labeled Wireless Sensor Network Data

International journal of computer science and information security, 2016-09, Vol.14 (9), p.917

2016

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Imputation by feature importance (IBFI): A methodology to envelop machine learning method for imputing missing patterns in time series data

Anomaly Classification for Earthquake Prediction in Radon Time Series Data Using Stacking and Automatic Anomaly Indication Function

Simulated Annealing-Based Image Reconstruction for Patients With COVID-19 as a Model for Ultralow-Dose Computed Tomography

Time Series Reconstruction With Feature-Driven Imputation: A Comparison of Base Learning Algorithms

Correction to: Anomaly Classification for Earthquake Prediction in Radon Time Series Data Using Stacking and Automatic Anomaly Indication Function

Analysis of Proposed and Traditional Boosting Algorithm with Standalone Classification Methods for Classifying Gene Expresssion Microarray Data Using a Reject Option

An Improved Imputation Method for Accurate Prediction of Imputed Dataset Based Radon Time Series

A Novel Hybrid Learning System Using Modified Breaking Ties Algorithm and Multinomial Logistic Regression for Classification and Segmentation of Hyperspectral Images

Classification of rocks radionuclide data using machine learning techniques

Imputation by feature importance

Multifractal detrended cross-correlation analysis of radioactivity borne radon, thoron and meteorological time series

K-means and K-medoids: Cluster Analysis on Birth Data Collected in City Muzaffarabad, Kashmir

Comparative Analysis of Boosting with other Machine Learning Methods for classifying Labeled Wireless Sensor Network Data

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